/*some changes per request of Ana*/ /*******************************************************************\ |Systemic Research Inc. | |Evaluation of Urban Systemic Initiative | |MakeFinal Tables based on Table of Contents | |SAS PROGRAM II for Tables and Graphs | |October 2001 -- February 2002 | |by Kazuaki Uekawa, Ph.D. | |Independent SAS consultant | |(kaz_uekawa@hotmail.com) | |http://www.src.uchicago.edu/users/ueka | |http://www.geocities.com/sastip | ********************************************************************/ /*Place a program "newlabel.sas" in the same folder.*/ /*specify your working directory (the path must end with separater, i.e., \ or /.) e.g., %let WD2=D:\systemic\ECB\; */ %let WD2=D:\systemic\ECB\; /*specify the directory which you want to use to store graphs produced by this program e.g., %let STORE=D:\systemic\ECB\; */ %let STORE=D:\systemic\ECB\; *footnote "draft kuekawa@systemic.com Dec 18 2001" ; libname here2 "&WD2"; options nodate; /*******************************************************************\ |Systemic Research Inc. | | Prepping data and graphing Exhibit II-1 to II-2 | by Kazuaki Uekawa, Ph.D. (kaz_uekawa@hotmail.com) | \*******************************************************************/ %macro system (group=, type=,taitoru1=,taitoru2=, name=,datasets=,legend=,cities1=,cities2=,cities3=,cities4=); data main;set here2.enrollment_CityYear; if city ne "Houston"; if city ne "Hypothetical"; if city ne "New Orleans"; /*don't use year 2000*/ if year ne 2000; /*imputation and eliminate cities when more than two years of data are missing*/ /*for cohort 93*/ imp_&group._alge1&type=" "; imp_&group._allsci&type=" "; imp_&group._himath&type=" "; imp_&group._grade8=" "; imp_&group._grade9to12=" "; if city="Baltimore" and year=1993 then do; total_himathe=6106; total_allscie=12497; imp_total_himathe="*"; imp_total_allscie="*"; end; if city="Detroit" and year=1993 then do; /* total_grade8=abs(mean(10978, 10679); imp_total_grade8="*"; */ ur_grade8=abs((19276+9975)/2); ur_grade9to12=abs((38525+37506)/2); imp_ur_grade8="*"; imp_ur_grade9to12="*"; end; if city="Detroit" and year=1996 then do; ur_grade8=abs((9975+9822)/2); ur_grade9to12=abs((37506+36605)/2); imp_ur_grade8="*"; imp_ur_grade9to12="*"; end; /*fix irregularity*/ if city ="Detroit" and year=1997 then do; ur_alge1e=1145/10; end; if city="Detroit" and (year=1998 or year=1999) then do; ur_grade8=abs((9899+9822)/2); ur_grade9to12=abs((37056+36605)/2); ur_himathe=abs((15362+25181)/2); ur_allscie=abs((16940+16489)/2); ur_alge1e=abs((114+150)/2); imp_ur_grade8="*"; imp_ur_grade9to12="*"; imp_ur_himathe="*"; imp_ur_allscie="*"; imp_ur_alge1e="*"; end; exclude_totale_data=0; if /*city ="Dallas" or*/ city ="Detroit" or city ="El Paso" or city ="Phenix" then do; exclude_totale_data=1; end; exclude_ure_data=0; if city= "Baltimore" or city="El Paso" then do; exclude_ure_data=1; end; exclude_totalc_data=0; if city="Baltimore" or city="El Paso" or city="Detroit" or city="Milwaukee" then do; exclude_totalc_data=1; end; exclude_urc_data=0; if city="Baltimore" or city="El Paso" or city="Detroit" or city="Phoenix" or city="Milwaukee" then do; exclude_urc_data=1; end; exclude_alge1E=0; if city="Cleveland" then do; exclude_alge1E=1; end; /* exclude_totalc_alge1_data=0; if city="Cleveland" then do; exclude_totalc_alge1_data=1; end;*/ *exclude_urc_data=0; /*for cohort 93*/ if city="Cleveland" and year=1994 then do; total_himathe=abs((4547+7497)/2); total_allscie=abs((5129+5266)/2); imp_total_himathe="*"; imp_total_allscie="*"; ur_himathe=abs((3643+6151/2)); imp_ur_himathe="*"; ur_allscie=abs((4118+4345/2)); imp_ur_allscie="*"; total_allscic=abs((3519+3676)/2); total_himathc=abs((2849+4327)/2); imp_total_himathc="*"; imp_total_allscic="*"; ur_allscic=abs(mean(2792 , 3007)); ur_himathc=abs(mean(2221 , 3479 )); imp_ur_himathc="*"; imp_ur_allscic="*"; end; if city="Cleveland" and year=1999 then do; total_himathe=10668; total_allscie=5474; total_grade9to12=16032; ur_himathe=abs(mean (4568, 8839)); ur_allscie=abs(mean(4853 , 4448)); ur_grade9to12=abs(mean(14053, 13140)); imp_total_himathe="*"; imp_total_allscie="*"; imp_total_grade9to12="*"; imp_ur_himathe="*"; imp_ur_allscie="*"; imp_ur_grade9to12="*"; total_allscic=abs(mean(4200 , 4018 )); total_himathc=abs(mean(3724 , 6759 )); imp_total_himathc="*"; imp_total_allscic="*"; ur_allscic=abs(mean(3224 ,3430)); ur_himathc=abs(mean(3007 ,5455 )); imp_ur_himathc="*"; imp_ur_allscic="*"; end; /*all cities for cohort 93 are used*/ /*cohort 95*/ if city="Milwaukee" and (year=1995 or year=1996) then do; total_himathe=abs(mean(2582 , 9204)); total_allscie=abs(mean( 3265, 9423)); total_alge1e=abs(mean( 1070, 1372 )); imp_total_himathe="*"; imp_total_allscie="*"; imp_total_alge1e="*"; ur_himathe=abs(mean(1761 ,6219)); ur_allscie=abs(mean( 2262, 6493)); ur_alge1e=abs(mean( 693, 966 )); imp_ur_himathe="*"; imp_ur_allscie="*"; imp_ur_alge1e="*"; end; /*to impute an irregular number*/ if city ="San Diego" and year=1997 then do; total_alge1e=abs(mean(9328, 10269)); imp_total_alge1e="*"; ur_alge1e=abs(mean( 4442, 5038 )); imp_ur_alge1e="*"; total_allscic=abs(mean( 12053 , 12582 )); total_himathc=abs(mean(10775 , 11587 )); total_alge1c=abs(mean(7940 , 8625 )); imp_total_himathc="*"; imp_total_allscic="*"; imp_total_alge1c="*"; ur_allscic=abs(mean(4714 , 4819 )); ur_himathc=abs(mean(3553 , 3958 )); ur_alge1c=abs(mean(3473 , 3858 )); imp_ur_himathc="*"; imp_ur_allscic="*"; imp_ur_alge1c="*"; end; if city ="San Diego" and year=1999 then do; total_alge1e=abs(mean( 9798.5, 10269)); imp_total_alge1e="*"; ur_alge1e=abs(mean( 4740, 5038 )); imp_ur_alge1e="*"; total_allscic=abs(mean( 12582 , 12317 )); total_himathc=abs(mean(11587 , 11181 )); total_alge1c=abs(mean(8625 , 8282 )); imp_total_himathc="*"; imp_total_allscic="*"; imp_total_alge1c="*"; ur_allscic=abs(mean(4768,4819 )); ur_himathc=abs(mean(3755.5 , 3958)); ur_alge1c=abs(mean(3663 , 3853)); imp_ur_himathc="*"; imp_ur_allscic="*"; imp_ur_alge1c="*"; end; *******************************************************; *******************************************************; /*Last minute removal of cities*/ /*Dallas has an error in Algebra data, so remove values here2*/ /*February 27th, 2002*/ if city="Dallas" then do; total_alge1e=.; ur_alge1e=.; end; /*We received some updated data from Baltimore. Apparently Math and Science Course Enrollment prior to 1996-1997 is not correct and are not available. */ /*march 3rd*/ if city="Baltimore" then do; total_himathe=.; total_allscie=.; total_himathc=.; total_allscic=.; ur_himathe=.; ur_allscie=.; ur_himathc=.; ur_allscic=.; end; *******************************************************; *******************************************************; /*cohort lables*/ if city= 'Hypothetical' or city='Chicago' or city='Baltimore' or city='Dallas' or city='Detroit' or city='El Paso' or city='Miami' or city='New York' or city='Phoenix' then do; /*give various cohort names for later convinience*/ cohort=1;cohort2=93;cohort_name="Cohort 93";end; if city='Cleveland' or city='Columbus' or city='Fresno' or city='Los Angeles' or city='Memphis' or city='New Orleans' or city='Philadelphia' then do;cohort=2;cohort2=94;cohort_name="Cohort 94";end; if city='Milwaukee' or city= 'St. Louis' or city= 'San Antonio' or city= 'San Diego' then do;cohort=3;cohort2=95;cohort_name="Cohort 95";end; if city='Atlanta' or city='Jacksonville' then do; cohort=4; cohort2=97;cohort_name="Cohort 97";end; if city='Houston' then do;cohort=5;cohort2=99;cohort_name="Cohort 99";end; /*Creating dummy indicators for cities to be used*/ /*here2 DECIDE WHICH CITIES TO INCLUDE*/ use_alge1=1; use_himath=1; use_allsci=1; proc sort data=main out=mainS;by cohort_name year;run; ***********; /*these are to provide raw data table after each graph*/ data confirm;set mainS; valid_algebra1=" ";if &group._alge1&type > -9 and &group._grade8 > -9 then valid_algebra1="#"; valid_highmath=" "; if &group._himath&type > -9 and &group._grade9to12 > -9 then valid_highmath="#"; valid_science=" "; if &group._allsci&type > -9 and &group._grade9to12 > -9 then valid_science="#"; run; proc means data=mainS noprint sum; by cohort_name year; where &group._himath&type > -9 and &group._grade9to12 > -9 and use_himath=1 and exclude_&group&type._data =0; var &group._himath&type &group._grade9to12; output out=mainSmath_M sum=; run; data math;length subject $ 13;set mainSmath_M; keep cohort_name year value prop subject _freq_; value=&group._himath&type; prop=&group._himath&type/&group._grade9to12; subject="High Math"; proc means data=mainS noprint sum; by cohort_name year; where &group._alge1&type > -9 and &group._grade8 > -9 and use_alge1=1 and exclude_&group&type._data =0 and exclude_alge1E =0 ; *var &group._himath&type &group._enroll_himath &group._allsci&type &group._enroll_allsci; var &group._alge1&type &group._grade8; output out=mainSalge_M sum=; run; data alge1;length subject $ 13;set mainSalge_M; keep cohort_name year value prop subject _freq_; value=&group._alge1&type; prop=&group._alge1&type/&group._grade8; subject="Algebra1"; proc means data=mainS noprint sum; where &group._allsci&type > -9 and &group._grade9to12 > -9 and use_allsci=1 and exclude_&group&type._data =0; by cohort_name year; *var &group._himath&type &group._enroll_himath &group._allsci&type &group._enroll_allsci; var &group._allsci&type &group._grade9to12 ; output out=mainSsci_M sum=; run; data science;length subject $ 13;set mainSsci_M; keep cohort_name year value prop subject _FREq_; value=&group._allsci&type; prop=&group._allsci&type/&group._grade9to12; Subject="Science"; run; data together;set &datasets; by cohort_name year; if year < 2000; under=" "; par1="("; par2=")"; prop2=INT(prop*100); perc="%"; dot=","; value1=INT(value/1000); value2=(value-(value1*1000)); value2c = put(value2,z3.); ID= compress(trim(value1)||dot||value2c||par1|| prop2||perc||par2); *LabelID=subject||cohort_name; LabelID=cohort_name||subject; drop under par1 par2 prop2 perc dot value1 value2 value2c ; run; proc sort data=together;by labelID;run; /*give the names of the cities used*/ proc transpose data=mainS out=mainS2; where &group._himath&type > -9 and &group._grade9to12 > -9 and use_himath=1 and exclude_&group&type._data =0; by cohort_name year;var city; run; data math;length cities_used $ 60;length subject $ 13;set mainS2; keep cohort_name year cities_used subject; cities_used=compress(trim(col1)||trim(col2)||trim(col3)||trim(col4)||trim(col5)||trim(col6)||trim(col7)||trim(col8)); subject="High Math"; run; proc transpose data=mainS out=mainS2; where &group._alge1&type > -9 and &group._grade8 > -9 and use_alge1=1 and exclude_&group&type._data =0 and exclude_alge1E=0 ; by cohort_name year;var city;run; data alge1;length cities_used $ 60; length subject $ 13; set mainS2; keep cohort_name year cities_used subject; cities_used=compress(trim(col1)||trim(col2)||trim(col3)||trim(col4)||trim(col5)||trim(col6)||trim(col7)||trim(col8)); subject="Algebra1"; run; proc transpose data=mainS out=mainS2; where &group._allsci&type > -9 and &group._grade9to12 > -9 and use_allsci=1 and exclude_&group&type._data =0; by cohort_name year;var city;run; data science;length cities_used $ 60;length subject $ 13;set mainS2; keep cohort_name year cities_used subject; cities_used=compress(trim(col1)||trim(col2)||trim(col3)||trim(col4)||trim(col5)||trim(col6)||trim(col7)||trim(col8)); subject="Science"; run; ************; data allnames; set &datasets;run; *by cohort_name year; %let color1=LIPB; %let color2=LIO; data putIDs;set together; *by cohort; by labelID; where value ^= .; retain xsys ysys '2' position '3' when 'a'; if first.labelID then do; function='label'; x=year; y=value; text=ID; size=2.5;output;end; if last.labelID then do; function='label'; x=year; y=value; text=ID; size=2.5; output;end; run; goptions reset=all device=gif GSFNAME=GIFOUT GSFMODE=replace gunit=pct cback=white /* htitle=3*/ htext=3.5 /* ftext=swiss*/ /*ftext=swissb ctext=blue*/ /*vsize=10 hsize=8*/; proc greplay nofs igout=work.gseg;delete _all_;run; *options nobyline ; goptions vsize=5 hsize=3.75 nodisplay; symbol1 i=join c=gold width=3 value=dot height=3.5 cv=gray; symbol2 i=join c=purple width=3 value=circle height=3.5 cv=black; *axis1 minor=none width=2 label=( height=4 a=90 r=0 "Number of Students" ) offset=(1); axis1 minor=none width=2 value=(height=4) label=( height=3 a=90 r=0 f=swissu "Number of Students" ) offset=(1); axis2 order=(1992 1993 to 1999 by 1 2000 2001 ) minor=none width=2 value= ( height=4 " " "93-94" "94-95" "95-96" "96-97" "97-98" "98-99" "99-00" " " " " ) label=(height=3 f=swissu "School Year"); /*fix this one. We don't want 2000*/ legend1 position=(left top inside) across=1 value=( tick=1 h=5 "Math Enrollment" tick=2 h=5 "Science Enrollment") label=none; legend2 position=(left top inside) across=1 value=( tick=1 h=5 "Algebra I" ) label=none; ***********************; footnote1 ; Filename GIFOUT "&store.&name cohort93.gif"; proc gplot data=together; title1 h=4 /*3.5 *//*f=swissu*/" Cohort 93"; title2 h=5 /*3.5*/ justify=center &cities1; title3 h=5 " *=Data imputed"; *footnote1 h=4 /* justify=left*/ "Baltimore, Chicago, Dallas, Miami, New York"; plot value*year=subject / vaxis=axis1 haxis=axis2 legend=&legend anno=putIDs ; *by cohort_name; where cohort_name="Cohort 93" and year ne 2000; format value comma10.0; run; Filename GIFOUT Clear; Filename GIFOUT "&STORE.&name cohort94.gif"; proc gplot data=together; title1 h=4 /*f=swissu*/ " Cohort 94"; title2 h=4.5 /*3.5*/ justify=center &cities2; title3 h=5 " *=Data imputed"; plot value*year=subject / vaxis=axis1 haxis=axis2 legend=&legend anno=putIDs ; *by cohort_name; where cohort_name="Cohort 94" and year ne 2000; format value comma10.0; run; Filename GIFOUT Clear; proc gplot data=together; title1 h=4 /* f=swissu*/ " Cohort 95"; title2 h=5 /*3.5*/ justify=center &cities3; title3 h=5 " *=Data imputed"; plot value*year=subject / vaxis=axis1 haxis=axis2 legend=&legend anno=putIDs ; *by cohort_name; *where cohort=3 and year ne 2000; where cohort_name="Cohort 95" and year ne 2000; format value comma10.0; run; proc gplot data=together; title1 h=4 /*f=swissu*/ " Cohort 97"; title2 h=5 /*3.5*/ justify=center &cities4; title3 h=5 " *=Data imputed"; plot value*year=subject / vaxis=axis1 haxis=axis2 legend=&legend anno=putIDs ; *by cohort_name; *where cohort=4 and year ne 2000; where cohort_name="Cohort 97" and year ne 2000; format value comma10.0; run; /*back to default*/ goptions vsize=0 hsize=0; proc gslide ; title1 h=2.5 "&name "; title2 h=2.5 "&taitoru1"; title3 h=2.5 "&taitoru2"; *footnote h=2.5"City name with *=Some data imputed"; *footnote1 h=3"Cohort93 (Baltimore, Chicago, Dallas, Miami, New York), Cohort 94 (Cleveland, Columbus, Fresno, LA, Memphis, and Philadelphia) "; *footnote2 h=3"Cohort95 (Milwaukee, San Antonio, San Diego, St. Louis), Cohort 94 (Atlanta, Jaksonville)"; run; /*turn display on*/ goptions display; /* create 5 panel template, treplay GPLOTs and GSLIDE into SPEC5 template */ Filename GIFOUT "&STORE.&name .gif"; proc greplay nofs igout=work.gseg tc=tempcat; tdef spec5 1/ llx=0 lly=45 ulx=0 uly=90 urx=50 ury=90 lrx=50 lry=45 2/ llx=0 lly=0 ulx=0 uly=45 urx=50 ury=45 lrx=50 lry=0 3/ llx=50 lly=45 ulx=50 uly=90 urx=100 ury=90 lrx=100 lry=45 4/ llx=50 lly=0 ulx=50 uly=45 urx=100 ury=45 lrx=100 lry=0 5/ llx=0 lly=0 ulx=0 uly=100 urx=100 ury=100 lrx=100 lry=0 ; template spec5; *treplay 1:gplot 2:gplot1 3:gplot2 4:gplot3 5:gslide; treplay 1:gplot 2:gplot2 3:gplot1 4:gplot3 5:gslide; run; quit; Filename GIFOUT Clear; *proc contents data=together; *run; *proc contents data=allnames; *run; proc sort data=allnames;by cohort_name year subject;run; proc sort data=together out=togetherB;by cohort_name year subject;run; data together2;merge togetherB allnames; by cohort_name year subject; *proc print data=together2; *var cohort_name year subject value cities_used; *run; proc sort data=together2 out=together3;by cohort_name subject year;run; ods rtf file="&STORE.&name..rtf" /* style=minimal*/; proc report data=together3 nowd headline colwidth=8 spacing=1; title1 "&name &taitoru1"; title2 "&taitoru2"; title3 "Raw Data: Statistics"; column cohort_name subject year value prop; *define /*cohort*/ / order order=data; define cohort_name /order order=data; define value / "N" format=comma10.0; define prop /"%" format= percent8.1; break after cohort_name/ skip ; run; proc report data=together3 nowd headline colwidth=8 spacing=0; title1 "&name &taitoru1"; title2 "&taitoru2"; title3 "Raw Data: Cities Used"; column cohort_name subject year cities_used; *define /*cohort*/ / order order=data; define cohort_name /order order=data; *define value / "N" format=comma10.0; break after cohort_name/ skip ; run; proc report data=confirm nowd headline colwidth=5 spacing=0; title1 "&name &taitoru1"; title2 "&taitoru2"; title3 "Check for Accuracy: By CITIES"; footnote1 "#=both denominator (&group. pop) and numerator (taker) for deriving a rate exist"; footnote2 "*=data imputed"; by cohort_name; column city year &group._grade8 imp_&group._grade8 &group._grade9to12 imp_&group._grade9to12 &group._alge1&type valid_algebra1 imp_&group._alge1&type &group._himath&type valid_highmath imp_&group._himath&type &group._allsci&type valid_science imp_&group._allsci&type ; define city /order order=data; define &group._grade8 / "8G" format=comma10.0; define &group._grade9to12/"9-12 G" format=comma10.0; define &group._alge1&type / "Alge1" format=comma10.0; define &group._himath&type / "H. math" format=comma10.0; define &group._allsci&type / "Sci."format=comma10.0; define valid_algebra1 /" " ; define valid_highmath /" " ; define valid_science /" " ; define imp_&group._alge1&type /" " ; define imp_&group._allsci&type /" " ; define imp_&group._himath&type /" " ; define imp_&group._grade9to12 /" " ; define imp_&group._grade8 /" " ; *break after year /dol summarize skip ; break after city /dol summarize skip ; run; proc report data=confirm nowd headline colwidth=5 spacing=0; title1 "&name &taitoru1"; title2 "&taitoru2"; title3 "Check for Accuracy: BY YEAR"; footnote1 "#=both denominator (&group. pop) and numerator (taker) for deriving a rate exist"; footnote2 "*=data imputed"; by cohort_name; column city year &group._grade8 imp_&group._grade8 &group._grade9to12 imp_&group._grade9to12 &group._alge1&type valid_algebra1 imp_&group._alge1&type &group._himath&type valid_highmath imp_&group._himath&type &group._allsci&type valid_science imp_&group._allsci&type; define year /order order=data; *define city /order order=data; define &group._grade8 / "8G" format=comma10.0; define &group._grade9to12/"9-12G" format=comma10.0; define &group._alge1&type / "Alge1" format=comma10.0; define &group._himath&type / "H. math" format=comma10.0; define &group._allsci&type / "Sci."format=comma10.0; define valid_algebra1 /" " ; define valid_highmath /" " ; define valid_science /" " ; define imp_&group._grade9to12 /" " ; define imp_&group._grade8 /" " ; define imp_&group._alge1&type /" " ; define imp_&group._allsci&type /" " ; define imp_&group._himath&type /" " ; break after year /dol summarize skip ; *break after city /dol summarize skip ; run; ods rtf close; %mend system ; %system (legend=legend1,datasets=math science,group=total,type=e,name=Exhibit III-1,taitoru1=Number of Students Enrolled in 9-12, taitoru2=Gate-Keeping and Higher-Level Mathematics and Science Courses, cities1=" Chicago, Dallas, Miami, NewYork", cities2=" Cleveland*,Columbus,Fresno,LA,Memphis,Philadelphia", cities3=" Milwaukee*, San Antonio, San Diego, St. Louis", cities4=" Atlanta, Jacksonville"); %system (legend=legend1,datasets=math science,group=ur,type=e,name=Exhibit III-2,taitoru1=Number of Underrepresented Minority Students Enrolled in Grade 9-12, taitoru2=Gate-Keeping and Higher-Level Mathematics and Science Courses, cities1=" Chicago, Dallas, Detroit*, Miami, NewYork", cities2=" Cleveland*,Columbus,Fresno,LA,Memphis,Philadelphia", cities3=" Milwaukee*, San Antonio,San Diego, St. Louis", cities4=" Atlanta, Jacksonville" ); %system (legend=legend1,datasets=math science,group=total,type=c,name=Exhibit III-3,taitoru1=Number of Students Successfully Completing Grade 9-12, taitoru2=Gate-Keeping and Higher-Level Mathematics and Science Courses, cities1=" Chicago, Dallas, Miami, NewYork", cities2=" Cleveland*,Columbus,Fresno,LA,Memphis,Philadelphia", cities3=" San Antonio, San Diego*, St. Louis", cities4=" Atlanta, Jacksonville" ); %system (legend=legend1,datasets=math science,group=ur,type=c,name=Exhibit III-4,taitoru1=Number of Underrepresented Minority Students , taitoru2=Successfully Completing Grade 9-12 Gate-Keeping and Higher-Level Mathematics and Science Courses, cities1=" Chicago, Dallas, Miami, New York", cities2=" Cleveland*,Columbus,Fresno,LA, Memphis,Philadelphia", cities3=" San Antonio, San Diego*, St. Louis", cities4=" Atlanta, Jacksonville"); %system (legend=legend2,datasets=alge1 ,group=total,type=e,name=Exhibit IV-1,taitoru1=Number of Students Enrolled in 8th Grade Algebra I , taitoru2= , cities1=" Chicago, Miami, NewYork", cities2=" Columbus,Fresno,LA,Memphis,Philadelphia", cities3=" Milwaukee*, San Antonio, SanDiego*", cities4=" Atlanta, Jacksonville" ); %system (legend=legend2,datasets=alge1 ,group=ur,type=e,name=Exhibit IV-2,taitoru1=Number of Underrepresented Minority Students Enrolled in 8th Grade Algebra I , taitoru2= , cities1=" Detroit*, Miami", cities2=" Columbus,Fresno,LA,Memphis,Philadelphia", cities3=" Milwaukee*, San Antonio, SanDiego*", cities4=" Atlanta, Jacksonville"); /*******************************************************************\ CAPTURING GAP TREND| | | | | | by Kazuaki Uekawa, Ph.D. (kaz_uekawa@hotmail.com) | \*******************************************************************/ *proc greplay nofs igout=work.gseg; *delete _all_; *run; /*here2 DOING AP MINORITY ANALYSIS Exihit VI-3 and VI4*/ /*FEB 18*/ *****************************; *proc contents data=here2.ap_cityyear; *run; proc contents data=here2.ap_cityyear; run; data for_ap;set here2.ap_cityyear; keep city year indian_n1k_APmathtaker black_n1k_APmathtaker hispanic_n1k_APmathtaker white_n1k_APmathtaker total_n1k_APmathtaker indian_n1k_APscitaker black_n1k_APscitaker hispanic_n1k_APscitaker white_n1k_APscitaker total_n1k_APscitaker indian_n1k_APcomptaker black_n1k_APcomptaker hispanic_n1k_APcomptaker white_n1k_APcomptaker total_n1k_APcomptaker /*these are not necessary, I think indian_grade11 indian_grade12 white_grade11 white_grade12 hispanic_grade11 hispanic_grade12 black_grade11 black_grade12 total_grade11 total_grade12*/ ; run; proc sort;by city year;run; proc contents data=for_ap;run; data mainB;merge main for_ap; by city year; %macro an (indian=); &indian._grade11and12=&indian._grade11+&indian._grade12; &indian._APmathtaker=((&indian._n1k_APmathtaker)/1000)*(&indian._grade11and12); &indian._APscitaker=((&indian._n1k_APscitaker)/1000)*(&indian._grade11and12); &indian._APcomptaker=((&indian._n1k_APcomptaker)/1000)*(&indian._grade11and12); %mend an; %an (indian=indian); %an (indian=black); %an (indian=hispanic); %an (indian=white); %an (indian=total); ur_apmathtaker=sum(of indian_apmathtaker hispanic_apmathtaker black_apmathtaker); ur_apscitaker=sum(of indian_apscitaker hispanic_apscitaker black_apscitaker); ur_apcomptaker=sum(of indian_apcomptaker hispanic_apcomptaker black_apcomptaker); ur_grade11and12=sum(of indian_grade11and12 hispanic_grade11and12 black_grade11and12 ); ur_n1k_apmathtaker=(ur_apmathtaker/ur_grade11and12)*1000; ur_n1k_apscitaker=(ur_apscitaker/ur_grade11and12)*1000; ur_n1k_apcomptaker=(ur_apcomptaker/ur_grade11and12)*1000; gap_apmathtaker=white_n1k_apmathtaker-ur_n1k_apmathtaker; gap_apscitaker=white_n1k_apscitaker-ur_n1k_apscitaker; gap_apcomptaker=white_n1k_apcomptaker-ur_n1k_apcomptaker; run; *proc print data=mainB; *where city="St. Louis"; *var city year hispanic_apmathtaker black_apmathtaker indian_apmathtaker hispanic_grade11and12 black_grade11and12 indian_grade11and12 ur_n1k_apmathtaker ; *white_n1k_apmathtaker total_n1k_apmathtaker; *run; %macro akitsu2 (subj=); proc sort data=mainB out=mainB2;by city year ;run; data mainB3;set mainB2; by city year; /*DO NOT USE THE YEAR 2000*/ if year < 2000; if year=1993 then school_year="93-94"; if year=1994 then school_year="94-95"; if year=1995 then school_year="95-96"; if year=1996 then school_year="96-97"; if year=1997 then school_year="97-98"; if year=1998 then school_year="98-99"; if year=1999 then school_year="99-00"; if year=2000 then school_year="00-01"; run; data mainB4;set mainB3; *if gap_&enroll._&kore > -9; if gap_&subj > -9; cate=cohort|| city ; proc sort data=mainB4 out=mainsortedB;by /*cohort city year*/cate;run; data main&subj;set mainSORTEDB;by cate /*cohort city year*/; if first.cate then do; first=1;end; if last.cate then do; last=1;end; if first=1 or last=1; %let carola=gap_&subj; lag_&carola=lag(&carola);if first.cate then do;lag_&carola=.;end; %let carola=total_&subj; lag_&carola=lag(&carola);if first.cate then do;lag_&carola=.;end; if last.cate then do; X=total_&subj-lag_total_&subj; if X > 0 then overall_improvement="Y"; if X <=0 then overall_improvement="N"; if X =. then overall_improvement=". "; Y=gap_&subj-lag_gap_&subj; if Y > 0 then gap_reduction="N"; if Y <=0 then gap_reduction="Y"; if Y = . then gap_reduction=". "; end; %mend akitsu2; %akitsu2 (subj=apmathtaker); %akitsu2 (subj=apscitaker); %akitsu2 (subj=apcomptaker); %macro abc2 (name=,variable=,taitoru1=,taitoru2=); ods rtf file="&STORE.&name timeplot.rtf"; proc timeplot data=main&variable; title1 "&name "; title2 "&taitoru1"; title3 "&taitoru2"; by cohort_name; plot UR_n1k_&variable white_n1k_&variable /overlay hiloc npp ref=.5 /* axis=0 to 1 by .029*/; id city school_year overall_improvement gap_reduction UR_n1k_&variable white_n1k_&variable; format UR_n1k_&variable white_n1k_&variable comma8.0; run; %mend abc2; %abc2 ( name=Exhibit VI-3,variable=apmathtaker,taitoru1=Mathematics Advanced Placement, taitoru2= Gap between Test-Taking Rates of Underrepresented and White Students); %abc2 ( name=Exhibit VI-4,variable=apscitaker,taitoru1=Science Advanced Placement, taitoru2= Gap between Test-Taking Rates of Underrepresented and White Students); *proc print data=mainapmathtaker; *var city year ur_n1k_apmathtaker white_n1k_apmathtaker gap_apmathtaker lag_gap_apmathtaker total_n1k_apmathtaker lag_total_apmathtaker overall_improvement gap_reduction; *run; *****************************; %macro akitsu (kore=,enroll=); proc sort data=main out=main2;by city year ;run; data main3;set main2; by city year; /*DO NOT USE THE YEAR 2000*/ if year < 2000; if year=1993 then school_year="93-94"; if year=1994 then school_year="94-95"; if year=1995 then school_year="95-96"; if year=1996 then school_year="96-97"; if year=1997 then school_year="97-98"; if year=1998 then school_year="98-99"; if year=1999 then school_year="99-00"; if year=2000 then school_year="00-01"; run; data main4;set main3; if gap_&enroll._&kore > -9; cate=cohort|| city ; proc sort data=main4 out=mainsorted;by /*cohort city year*/cate;run; data main&kore&enroll;set mainSORTED;by cate /*cohort city year*/; if first.cate then do; first=1;end; if last.cate then do; last=1;end; if first=1 or last=1; %let carola=gap_&enroll._&kore; lag_&carola=lag(&carola);if first.cate then do;lag_&carola=.;end; %let carola=total_&enroll._&kore; lag_&carola=lag(&carola);if first.cate then do;lag_&carola=.;end; if last.cate then do; X=total_&enroll._&kore-lag_total_&enroll._&kore; if X > 0 then overall_improvement="Y"; if X <=0 then overall_improvement="N"; if X =. then overall_improvement=". "; Y=gap_&enroll._&kore-lag_gap_&enroll._&kore; if Y > 0 then gap_reduction="N"; if Y <=0 then gap_reduction="Y"; if Y = . then gap_reduction=". "; end; *proc print data=main&kore&enroll; *var cohort city year UR_&enroll._&kore white_&enroll._&kore overall_improvement_&kore gap_reduction_&kore; *run; %mend akitsu; %akitsu (kore=alge1,enroll=enroll); %akitsu (kore=himath,enroll=enroll); %akitsu (kore=allsci,enroll=enroll); *%akitsu (kore=alge1,enroll=enroll); %akitsu (kore=himath,enroll=compl); %akitsu (kore=allsci,enroll=compl); title1; title2; title3; title4; footnote1; footnote2; %macro abc (name=,variable=,taitoru1=,taitoru2=,enroll=,type=,denom=); ods rtf file="&STORE.&name timeplot.rtf"; *ods trace on; proc timeplot data=main&variable&enroll; title1 "&name "; title2 "&taitoru1"; title3 "&taitoru2"; by cohort_name; plot UR_&enroll._&variable white_&enroll._&variable /overlay hiloc npp ref=.5 /* axis=0 to 1 by .029*/; id city school_year overall_improvement gap_reduction UR_&enroll._&variable white_&enroll._&variable; format UR_&enroll._&variable white_&enroll._&variable percent8.0; run; proc report data=main&variable&enroll nowd headline colwidth=5 spacing=1; title4 "GAP statistics--Check for Accuracy in Consructing Gap Statistics" ; column cohort_name year city black_&variable&type hispanic_&variable&type native_&variable&type ur_&variable&type white_&variable&type ur_&denom white_&denom UR_&enroll._&variable white_&enroll._&variable gap_&enroll._&variable; define city /order order=data; define black_&variable&type/ "black" format=comma10.0; define hispanic_&variable&type/ "hispanic"format=comma10.0; define native_&variable&type/"native" format=comma10.0; define ur_&variable&type/ "UR"format=comma10.0; define white_&variable&type/ "white"format=comma10.0; define ur_&denom/ "URpop" format=comma10.0; define white_&denom/ "WhitePop" format=comma10.0; define UR_&enroll._&variable /"UR rate" format=percent8.1; define white_&enroll._&variable/ "White rate" format=percent8.1; define gap_&enroll._&variable/"GAP" format=percent8.1; /* define white_&variable&type/"white" format=comma10.0; define black_&variable&type/"black " format=comma10.0; define hispanic_&variable&type /"hisp " format=comma10.0; define native_&variable&type /"native " format=comma10.0; define ur_&variable&type /"UR" format=comma10.0; define ur_grade8 /"UR pop" format=comma10.0; define ur_grade9to12 /"UR pop" format=comma10.0; define white_grade8 /"white pop" format=comma10.0; define white_grade9to12 /"white pop " format=comma10.0; define black_&enroll._&variable /"Black rate" format=percent8.1; define hispanic_&enroll._&variable /"Hispanic rate" format=percent8.1; define UR_&enroll._&variable /"UR rate" format=percent8.1; define white_&enroll._&variable /"White rate" format=percent8.1; define gap_&enroll._&variable /"Gap this year" format=percent8.1; define lag_gap_&enroll._&variable /"Gap last year"format=percent8.1; define gap_reduction /"Reduced?"; define total_&enroll._&variable /"Whole sample rate" format=percent8.1; define lag_total_&enroll._&variable /"lagged whole sample rate" format=percent8.1; define overall_improvement / "Improved?";*/ break after city / /*dol summarize*/ skip ; run; proc report data=main&variable&enroll nowd headline colwidth=8 spacing=1; title4 "GAP statistics--informing whether gap reduced"; column cohort_name year city UR_&enroll._&variable white_&enroll._&variable gap_&enroll._&variable lag_gap_&enroll._&variable gap_reduction /* total_&enroll._&variable lag_total_&enroll._&variable overall_improvement_&variable*/ ; *define /*cohort*/ / order order=data; define city /order order=data; define UR_&enroll._&variable /"UR rate" format=percent8.1; define white_&enroll._&variable /"White rate" format=percent8.1; define gap_&enroll._&variable /"Gap this year" format=percent8.1; define lag_gap_&enroll._&variable /"Gap last year"format=percent8.1; define gap_reduction /"Reduced?"; define total_&enroll._&variable /"Whole sample rate" format=percent8.1; define lag_total_&enroll._&variable /"lagged whole sample rate" format=percent8.1; define overall_improvement / "Improved?"; break after city / /*dol summarize*/ skip ; *define total_alge1e valid_algebra1 total_himathe valid_highmath total_allscie valid_science / display; run; proc report data=main&variable&enroll nowd headline colwidth=8 spacing=1; title4 "About Total Enrollment--informing whether overall rate improved"; column cohort_name year city /* UR_&enroll._&variable white_&enroll._&variable gap_&enroll._&variable lag_gap_&enroll._&variable gap_reduction_&variable */ total_&enroll._&variable lag_total_&enroll._&variable overall_improvement ; *define /*cohort*/ / order order=data; define city /order order=data; define UR_&enroll._&variable /"UR rate" format=percent8.1; define white_&enroll._&variable /"White rate" format=percent8.1; define gap_&enroll._&variable /"Gap this year" format=percent8.1; define lag_gap_&enroll._&variable /"Gap last year"format=percent8.1; define gap_reduction /"Reduced?"; define total_&enroll._&variable /"Whole sample rate" format=percent8.1; define lag_total_&enroll._&variable /"lagged whole sample rate" format=percent8.1; define overall_improvement / "Improved?"; break after city / /*dol summarize*/ skip ; *define total_alge1e valid_algebra1 total_himathe valid_highmath total_allscie valid_science / display; run; ods rtf close; %mend abc; %abc ( name=Exhibit IV-3,variable=alge1,enroll=enroll,taitoru1=Algebra I in 8th Grade Course Enrollment, taitoru2= Gap between Passing Rate of Largest Minority Group and White Students,type=e,denom=grade8); %abc ( name=Exhibit III-5,variable=himath,enroll=enroll,taitoru1=Gate-Keeping and Higher-Level Mathematics Course Enrollment, taitoru2= Gap between Enrollment Rates of Underrepresented and White Students,type=e,denom=grade9to12); %abc ( name=Exhibit III-6,variable=allsci,enroll=enroll,taitoru1=Gate-Keeping and Higher-Level Science Course Enrollment, taitoru2=Gap between Enrollment Rates of Underrepresented and White Students,type=e,denom=grade9to12); %abc ( name=Exhibit III-7,variable=himath,enroll=compl,taitoru1=Gate-Keeping and Higher-Level Mathematics Course Completion, taitoru2= Gap between Enrollment Rates of Underrepresented and White Students,type=c,denom=grade9to12); %abc ( name=Exhibit III-8,variable=allsci,enroll=compl,taitoru1=Gate-Keeping and Higher-Level Science Course Completion, taitoru2= Gap between Successful Completion Rates of Underrepresented and White Students,type=c,denom=grade9to12); /*******************************************************************\ | AP Prepping | | | | | | by Kazuaki Uekawa, Ph.D. (kaz_uekawa@hotmail.com) | \*******************************************************************/ *; data ap;set here2.ap_cityyear; if city="Miami-Dade" then city="Miami"; if city ne "Houston"; if city= 'Hypothetical' or city='Chicago' or city='Baltimore' or city='Dallas' or city='Detroit' or city='El Paso' or city='Miami' or city='New York' or city='Phoenix' then do; /*give various cohort names for later convinience*/ cohort=1;cohort2=93;cohort_name="Cohort 93";end; if city='Cleveland' or city='Columbus' or city='Fresno' or city='Los Angeles' or city='Memphis' or city='New Orleans' or city='Philadelphia' then do;cohort=2;cohort2=94;cohort_name="Cohort 94";end; if city='Milwaukee' or city= 'St. Louis' or city= 'San Antonio' or city= 'San Diego' then do;cohort=3;cohort2=95;cohort_name="Cohort 95";end; if city='Atlanta' or city='Jacksonville' then do; cohort=4; cohort2=97;cohort_name="Cohort 97";end; if city='Houston' then do;cohort=5;cohort2=99;cohort_name="Cohort 99";end; /*elimiating cities when they are missing data in some years*/ if city="Detroit" or city="Phoenix" then do; apmathtaker=.; apscitaker=.; apcomptaker=.; end; /*missing flags*/ %macro gon2 (var=); flag_&var=0; if &var >-9 and total_grade11and12 > -9 then do; flag_&var=1; end; %mend gon2; %gon2 (var=APmathtaker); %gon2 (var=APscitaker); %gon2 (var=APcomptaker); %gon2 (var= apmathscore3 ); %gon2 (var=apsciscore3); %gon2 (var= apcompscore3); proc sort;by cohort_name year;run; %macro gon (var=); proc means data=ap noprint sum; where &var > -9 and total_grade11and12 > -9; by cohort_name year; var &var total_grade11and12; output out=&var sum=; run; %mend gon; %gon (var=APmathtaker); %gon (var=APscitaker); %gon (var=APcomptaker); %gon (var= apmathscore3 ); %gon (var=apsciscore3); %gon (var= apcompscore3); data ap_sum; merge apmathtaker apscitaker apcomptaker apmathscore3 apsciscore3 apcompscore3; by cohort_name year; *proc print data=apmathtaker; *run; data ap_mean;set ap_sum; %macro arya (var=); N1K_AP&var=1000*(AP&var/total_grade11and12); %mend arya ; %arya (var=mathtaker); %arya (var=scitaker); %arya (var=comptaker); %macro arya2 (var=); total_N1K_AP&var=1000*(AP&var/total_grade11and12); %mend arya2 ; %arya2 (var=mathscore3); %arya2 (var=sciscore3); %arya2 (var=compscore3); N1K_APmathtaker=round(N1K_APmathtaker,.1) ; N1K_APscitaker=round(N1K_APscitaker,.1) ; N1K_APcomptaker=round(N1K_APcomptaker,.1) ; total_n1k_apmathscore3=round(total_n1k_apmathscore3,.1) ; total_n1k_apsciscore3=round(total_n1k_apsciscore3,.1) ; total_n1k_apcompscore3=round(total_n1k_apcompscore3,.1) ; drop apmathtaker apscitaker apcomptaker apmathscore3 apsciscore3 apcompscore3 _type_ _freq_; *proc print data=ap_mean; *run; /*******************************************************************\ | AP Score | | | | | | | by Kazuaki Uekawa, Ph.D. (kaz_uekawa@hotmail.com) | \*******************************************************************/ *goptions reset=all device=gif GSFNAME=GIFOUT GSFMODE=replace gunit=pct cback=white /* htitle=3*/ htext=3.5 /*ftext=swissb ctext=blue*/ /*vsize=10 hsize=8*/; proc greplay nofs igout=work.gseg;delete _all_;run; *options nobyline ; goptions vsize=5 hsize=3.75 nodisplay; * goptions reset=all device=gif GSFNAME=GIFOUT GSFMODE=replace; goptions reset=all device=gif GSFNAME=GIFOUT GSFMODE=replace gunit=pct cback=white /* htitle=3*/ htext=5/*ftext=swissb ctext=blue*/ /*vsize=10 hsize=8*/; /*start here2*/ %macro these (keyvar=,taitoru1=); data ap_mean2;set ap_mean; ID2=round(&keyvar,.01); ID=put(ID2,4.1); run; data putIDs;set ap_mean2; *by cohort; by cohort_name; where &keyvar ^= .; retain xsys ysys '2' position '3' when 'a'; if first.cohort_name then do; function='label'; x=year; y=&keyvar; text=ID; size=3;output;end; if last.cohort_name then do; function='label'; x=year; y=&keyvar; text=ID; size=3; output;end; run; data &keyvar;set ap_mean; by cohort_name;where &keyvar ^= .; retain xsys ysys '2' position '3' when 'a'; if last.cohort_name then do;function='label'; x=year; y=&keyvar; text=cohort_name; output;end; run; legend1 position=(left top inside) across=1 /*value=( tick=1 "Math Enrollment" tick=2 "Science Enrollment")*/ label=none; symbol1 i=join c=yellow width=2 value=dot height=2 /*pointlabel=(h=5 "#&keyvar")*/; symbol2 i=join c=green width=2 value=dot height=2 /*pointlabel=(h=5 "#&keyvar")*/; symbol3 i=join c=blue width=2 value=dot height=2 /*pointlabel=(h=5 "#&keyvar")*/; symbol4 i=join c=red width=2 value=dot height=2 /*pointlabel=(h=5 "#&keyvar")*/; axis1 label=( a=90 r=0) offset=(1); *axis2 order=(1993 to 2000 by 1) minor=none width=2; axis2 order=(1993 to 2001 by 1 ) minor=none width=2 value= ( "93-94" "94-95" "95-96" "96-97" "97-98" "98-99" "99-00" "00-01" " " ) label=("School Year"); *axis2 order=(1994 to 2000 by 1 ) minor=none width=2 value= (" " "93-94" "94-95" "95-96" "96-97" "97-98" "98-99" "99-00" " " " " ) label=("School Year"); axis1 /*order=(0 to 15000 by 10000, 20000 to 600000 by 100000 )*/ minor=none width=2 label=(a=90 r=0 f=swiss "Number of Students") offset=(1); %let name1=Exhibit VI-1&2; Filename GIFOUT "&STORE.&name1 &keyvar..gif"; proc gplot data=ap_mean; *where year ne 2000; title1 h=5 "&taitoru1"; plot &keyvar*year=cohort_name / vaxis=axis1 haxis=axis2 legend=legend1 annotate=putIDs; label &keyvar="Test-Takers per 1,000"; run; quit; %mend these; %these (keyvar=N1K_apmathtaker,taitoru1=Rate of Taking AP Mathematics Test); %these(keyvar=N1K_apscitaker,taitoru1=Rate of Taking AP Science Test); %these(keyvar=N1K_apcomptaker,taitoru1=Rate of Taking AP Computer Science Test); %these(keyvar=total_n1k_apmathscore3,taitoru1=AP Mathematics Test Scoring Above 3); %these(keyvar=total_n1k_apsciscore3,taitoru1=AP Science Test Scoring Above 3); %these(keyvar=total_n1k_apcompscore3,taitoru1=AP Computer Science Test Scoring Above 3); %macro dummy3; ods rtf file="&STORE.&name1..rtf" /* style=minimal*/; proc report data=ap_mean nowd headline colwidth=8 spacing=1; column cohort_name year &keyvar; define city /order order=data " "; define cohort_name/ order order=data " "; define &keyvar /display "AP math taker: individual weight=1"; *define &var1._NW/display "SAT math score: city weight=1"; break after cohort_name/ skip ; run; proc report data=ap nowd headline colwidth=8 spacing=1; column cohort_name city year &keyvar; define city /order order=data " "; define cohort_name/ order order=data " "; define &keyvar /display "AP math taker: individual weight=1"; *define &var1._NW/display "SAT math score: city weight=1"; break after cohort_name/ skip ; run; ODS RTF CLOSE; %mend; %let name1=Exhibit VI-1; /*back to default*/ goptions vsize=0 hsize=0; proc gslide ; title1 h=3 "&name1 "; title2 h=3 "Trends in Mathematics and Science Advanced Placement Tests Taken"; title3 h=3 "per 1,000 11th and 12th Grade Students"; run; %let name2=Exhibit VI-2; /*back to default*/ goptions vsize=0 hsize=0; proc gslide ; title1 h=3 "&name2 "; title2 h=3 "Trends in Mathematics and Science Advanced Placement Tests Taken"; title3 h=3 "Scoring above 3 per 1,000 11th and 12th Grade Students"; run; proc gslide ; title h=5 justify=left "Notes"; note h=5 justify=left "Cohort 93 (Yellow line)"; note h=5 justify=left "Baltimore, Chicago, Dallas, El Paso, Miami, New York"; note h=5 justify=left "(Detroit and Phoenix not used)"; note " "; note h=5 justify=left "Cohort 94 (Green line)"; note h=5 justify=left "Cleveland, Columbus, Fresno, Los Angeles, Memphis"; note h=5 justify=left "New Orleans, Philadelphia"; note " "; note h=5 justify=left "Cohort 95 (Blue line)"; note h=5 justify=left "Milwaukee, San Antonio, San Diego, St. Louis"; note " "; note h=5 justify=left "Cohort 97 (Red line) "; note h=5 justify=left "Atlanta, Jacksonville "; run; /*turn display on*/ goptions display; /* create 5 panel template, treplay GPLOTs and GSLIDE into SPEC5 template */ Filename GIFOUT "&STORE.&name1 .gif"; proc greplay nofs igout=work.gseg tc=tempcat; tdef spec5 1/ llx=0 lly=45 ulx=0 uly=90 urx=50 ury=90 lrx=50 lry=45 2/ llx=0 lly=0 ulx=0 uly=45 urx=50 ury=45 lrx=50 lry=0 3/ llx=50 lly=45 ulx=50 uly=90 urx=100 ury=90 lrx=100 lry=45 4/ llx=50 lly=0 ulx=50 uly=45 urx=100 ury=45 lrx=100 lry=0 5/ llx=0 lly=0 ulx=0 uly=100 urx=100 ury=100 lrx=100 lry=0 ; template spec5; treplay 1:gplot 2:gplot2 3:gplot1 4:gslide2 5:gslide; run; quit; Filename GIFOUT Clear; /* create 5 panel template, treplay GPLOTs and GSLIDE into SPEC5 template */ Filename GIFOUT "&STORE.&name2 .gif"; proc greplay nofs igout=work.gseg tc=tempcat; tdef spec5 1/ llx=0 lly=45 ulx=0 uly=90 urx=50 ury=90 lrx=50 lry=45 2/ llx=0 lly=0 ulx=0 uly=45 urx=50 ury=45 lrx=50 lry=0 3/ llx=50 lly=45 ulx=50 uly=90 urx=100 ury=90 lrx=100 lry=45 4/ llx=50 lly=0 ulx=50 uly=45 urx=100 ury=45 lrx=100 lry=0 5/ llx=0 lly=0 ulx=0 uly=100 urx=100 ury=100 lrx=100 lry=0 ; template spec5; treplay 1:gplot3 2:gplot5 3:gplot4 4:gslide2 5:gslide1; run; quit; Filename GIFOUT Clear; ods rtf file="&STORE.&name1 &name2 .rtf" /* style=minimal*/; proc report data=ap_mean nowd headline colwidth=5 spacing=1; title1 "&name1 & &name2"; title2 "AP test takers "; title3 ""; title4 "AP Raw data" ; column cohort_name year N1K_apmathtaker N1K_apscitaker N1K_apcomptaker total_n1k_apmathscore3 total_n1k_apsciscore3 total_n1k_apcompscore3;; define cohort_name /order order=data; define N1K_apmathtaker /"math taker " format=comma10.2; define N1K_apscitaker /"Sci taker " format=comma10.2; define N1K_apcomptaker/"Comp taker " format=comma10.2; define total_n1k_apmathscore3/"math score > 3 " format=comma10.2; define total_n1k_apsciscore3/"sci score > 3 " format=comma10.2; define total_n1k_apcompscore3/"comp score > 3 " format=comma10.2; break after cohort_name / /*dol summarize*/ skip ; run; %macro london (taitoru=, top=,apmathtaker=); data ap2;set ap; realN=((&top.N1K_&apmathtaker)/1000)*total_grade11and12; *proc print data=ap2; *var realN;*run; proc report data=ap2 nowd headline colwidth=8 spacing=1; title4 "AP data &taitoru : Check for Accuracy" ; where flag_&apmathtaker=1; column cohort_name year city &top.N1K_&apmathtaker total_grade11and12 realN N1K; define cohort_name /order order=data; define year /order order=data; define &top.n1k_&apmathtaker/format=comma10.0 ; define total_grade11and12/ format=comma10.0 "Population G11 & G12"; define realN/ format=comma10.0 "N. of Test Takers"; define N1K/computed format=comma10.2/*percent8.2*/ "N per 1000"; break after year / dol summarize skip ; compute n1k; n1k=(realN.sum/total_grade11and12.sum)*1000; endcomp; run; %mend london; %london (taitoru=Math Taker,top=total_,apmathtaker=apmathtaker); %london (taitoru=Science Taker,top=total_,apmathtaker=apscitaker); %london (taitoru=Computer Taker,top=total_,apmathtaker=apcomptaker); %london (taitoru=Math Score over 3,top=total_,apmathtaker=apmathscore3); %london (taitoru=Science Score over 3,top=total_,apmathtaker=apsciscore3); %london (taitoru=Comp Score over 3,top=total_,apmathtaker=apcompscore3); ods rtf close; /*******************************************************************\ | SAT and ACT data | | Get test score cohort means, both weighted and non-weighted | | | | | | | | by Kazuaki Uekawa, Ph.D. (kaz_uekawa@hotmail.com) | \*******************************************************************/ proc greplay nofs igout=work.gseg; delete _all_; run; /*merge data*/ data satact2;length city $ 15; set here2.sat_act_CITYYEAR; if city ne "Houston"; FLAG=1; *************************************************; /*Although this looks somewhat unnecessary, I give these cohort IDs to SATACT data because the other data to which SACTACT is merged to has missing in COHORT data, which causes some inconviniency*/ /*get actual year data is about... varies depeding on cohort*/ if city= 'Hypothetical' or city='Chicago' or city='Baltimore' or city='Dallas' or city='Detroit' or city='El Paso' or city='Miami' or city='New York' or city='Phoenix' then do; /*give various cohort names for later convinience*/ cohort=1;cohort2=93;cohort_name="Cohort 93";end; if city='Cleveland' or city='Columbus' or city='Fresno' or city='Los Angeles' or city='Memphis' or city='New Orleans' or city='Philadelphia' then do;cohort=2;cohort2=94;cohort_name="Cohort 94";end; if city='Milwaukee' or city= 'St. Louis' or city= 'San Antonio' or city= 'San Diego' then do;cohort=3;cohort2=95;cohort_name="Cohort 95";end; if city='Atlanta' or city='Jacksonville' then do; cohort=4; cohort2=97;cohort_name="Cohort 97";end; if city='Houston' then do;cohort=5;cohort2=99;cohort_name="Cohort 99";end; *************************************************; proc sort;by city year; data enrollment;set here2.enrollment_CITYYEAR; keep city year total_grade12; cohort=cohort2; /*imputing some data*/ if city="Detroit" and year=1993 then do; total_grade12=mean( 5800, 5432); end; /*Phoenix is missing to many on this, but because the 12th grade population seems stable, I justify the imputation*/ if city ="Phoenix" and (year=1995 or year=1996) then do; total_grade12=mean(4706, 4798); end; if city="Phoenix" and year=1998 then do; total_grade12=mean(4569, 4752); end; proc sort;by city year; /*for simple cohort means*/ data satact3;merge satact2 enrollment; by city year; if FLAG=1; N1K_acttaker=1000*(total_acttaker/total_grade12); N1K_sattaker=1000*(total_sattaker/total_grade12); proc sort data=satact3 out=satact3S;by cohort_name year;run; proc means data=satact3S noprint mean; by cohort_name year; var total_satmath total_satverb total_actmath total_actsci N1K_acttaker N1K_sattaker; output out=cohort_taker mean= total_satmath_NW total_satverb_NW total_actmath_NW total_actsci_NW N1K_acttaker_NW N1K_sattaker_NW; run; data cohort_taker;set cohort_taker; keep cohort_name year N1K_acttaker_NW N1K_sattaker_NW total_satmath_NW total_satverb_NW total_actmath_NW total_actsci_NW; total_satmath_NW =round(total_satmath_NW,.01) ; total_satverb_NW =round(total_satverb_NW,.01); total_actmath_NW =round(total_actmath_NW,.001) ; total_actsci_NW=round(total_actsci_NW,.001); N1K_acttaker_NW=round(N1K_acttaker_NW,1); N1K_sattaker_NW=round(N1K_sattaker_NW,1); /*for weighted cohort means*/ /*(by giving equal weight of 1 to every subject in the cities*/ /*In case sat and act have different patterns of missing data, I treat them separately and then merge them back to one data*/ data satact3S2;set satact3S; keep cohort_name year city total_actmath total_actsci total_acttaker total_grade12 total_satmath total_satverb total_sattaker SM_satmath SM_satverb SM_actmath SM_actsci ; /*get sum of multiples: necesasry ingredients for weighted mean scores, to be devided by sum of N*/ SM_satmath=total_satmath*total_sattaker; SM_satverb=total_satverb*total_sattaker; SM_actmath=total_actmath*total_acttaker; SM_actsci=total_actsci*total_acttaker; /*Because of "where total_acttkaer ne . ...." in proc mean lines, the years before the program starts will be kicked out, which is why weighted values derived here2 start only from the year that USI started in each city*/ proc means data=satact3S2 noprint sum;where total_acttaker ne . and total_grade12 ne .; by cohort_name year;var total_actmath total_actsci total_acttaker total_grade12 SM_actmath SM_actsci;output out=cohort_taker_W1 sum=; proc means data=satact3S2 noprint sum;where total_sattaker ne . and total_grade12 ne .; by cohort_name year;var total_satmath total_satverb total_sattaker total_grade12 SM_satmath SM_satverb;output out=cohort_taker_W2 sum=; data cohort_taker_W;merge cohort_taker_W1 cohort_taker_W2;by cohort_name year; data cohort_taker_W;set cohort_taker_W; keep cohort_name year N1K_acttaker N1K_sattaker total_satmath total_satverb total_actmath total_actsci; N1K_acttaker=INT(1000*(total_acttaker/total_grade12)); N1K_sattaker=INT(1000*(total_sattaker/total_grade12)); total_satmath=round(SM_satmath/total_sattaker,0.1); total_satverb=round(SM_satverb/total_sattaker,0.1); total_actmath=round(SM_actmath/total_acttaker, 0.01); total_actsci=round(SM_actsci/total_acttaker, 0.01); data cohort_taker_final;merge cohort_taker cohort_taker_W;by cohort_name year; *proc print data=cohort_taker_final; *run; run; /*******************************************************************\ | ACT Math test scores | | *graph | | *raw data table | | | | | | by Kazuaki Uekawa, Ph.D. (kaz_uekawa@hotmail.com) | \*******************************************************************/ proc greplay nofs igout=work.gseg; delete _all_;run; goptions vsize=5 hsize=3.75 nodisplay reset=all device=gif GSFNAME=GIFOUT GSFMODE=replace gunit=pct cback=white /* htitle=3*/ htext=4/*ftext=swissb ctext=blue*/ /*vsize=10 hsize=8*/; %macro sudan (var1=, name=,taitoru1=,horizon=); legend1 position=(left top inside) across=1 /*value=( tick=1 "Math Enrollment" tick=2 "Science Enrollment") */ label=none ; *legend1 label=none; symbol1 i=join c=yellow width=2 value=dot height=1 pointlabel=(h=5 "#&var1"); symbol2 i=join c=green width=2 value=dot height=1 pointlabel=(h=5 "#&var1"); symbol3 i=join c=blue width=2 value=dot height=1 pointlabel=(h=5 "#&var1"); symbol4 i=join c=red width=2 value=dot height=1 pointlabel=(h=5 "#&var1"); *axis1 label=( a=90 r=0) offset=(1); axis1 minor=none width=2 value=(height=4) label=( height=4 a=90 r=0 f=swissu "&horizon" ) offset=(1); /*start here2*/ *axis2 order=(1992 1993 to 1999 by 1 2000 2001 ) minor=none width=2 value= ( height=4 " " "93-94" "94-95" "95-96" "96-97" "97-98" "98-99" "99-00" " " " " ) label=(height=3 f=swissu "School Year"); *axis2 order=(1993 to 2000 by 1) minor=none width=2; axis2 order=(1993 to 2000 by 1) minor=none width=2 value= ( "93-94" "94-95" "95-96" "96-97" "97-98" "98-99" "99-00" "00-01") label=(height=4 f=swissu "School Year"); *Filename GIFOUT "&STORE.&name..gif"; proc gplot data=cohort_taker_final; title1 h=5 "&name"; title2 h=5 &taitoru1 ; *footnote1 "ACT sites are: Cohort 93 ...(see p.25 of AEAS)"; plot &var1*year=cohort_name / vaxis=axis1 haxis=axis2 legend=legend1 /*anno=addlable*/;/*USE THIS ANNOTE then series get legends right next to it*/ label &var1="&horizon" ; run; *title4; *quit; *Filename GIFOUT Clear; ods rtf file="&STORE.&name..rtf" /* style=minimal*/; proc report data=cohort_taker_final nowd headline colwidth=8 spacing=1; title1 "&name"; title2 &taitoru1 ; title3 "RAW DATA"; column cohort_name year &var1; define cohort_name/ order order=data " "; define &var1 /display "Value"; break after cohort_name/ skip ; run; ods rtf close; *goptions reset=all device=gif GSFNAME=GIFOUT GSFMODE=replace gunit=pct cback=white /* htitle=3*/ htext=4/*ftext=swissb ctext=blue*/ /*vsize=10 hsize=8*/; /*back to default*/ %mend sudan; %sudan (var1=n1k_sattaker,name=Exhibit VII-1,taitoru1="Number of SAT Test Takers per 1,000 12th Grade Students",horizon=Number of Students); %sudan (var1=total_satmath,name=Exhibit VII-2,taitoru1="Trends in SAT Mathematics Mean Scores",horizon=Cohort Mean Score); %sudan (var1=total_satverb,name=Exhibit VII-3,taitoru1="Trends in SAT verbal Mean Scores",horizon=Cohort Mean Score); %sudan (var1=n1k_acttaker,name=Exhibit VIII-1,taitoru1="Number of ACT Test Takers per 1,000 12th Grade Students",horizon=Number of Students); %sudan (var1=total_actmath,name=Exhibit VIII-2,taitoru1="Trends in ACT Mathematics Mean Scores",horizon=Cohort Mean Score); %sudan (var1=total_actsci,name=Exhibit VIII-3,taitoru1="Trends in ACT Science Reasoning Mean Scores",horizon=Cohort Mean Score); goptions vsize=0 hsize=0; proc gslide ; title1 h=3 "SECTION VII: SAT"; run; /*turn display on*/ proc gslide ; title1 h=3 "SECTION VIII: ACT"; run; proc gslide ; title h=5 justify=left "Notes"; note h=5 justify=left "Cohort 93 (Yellow line)"; note h=5 justify=left "Baltimore, Chicago, Dallas, Detroit, El Paso, Miami "; note h=5 justify=left "New York,Phoenix"; note " "; note h=5 justify=left "Cohort 94 (Green line)"; note h=5 justify=left "Cleveland, Columbus, Fresno, Los Angeles, Memphis"; note h=5 justify=left "New Orleans, Philadelphia"; note " "; note h=5 justify=left "Cohort 95 (Blue line)"; note h=5 justify=left "Milwaukee, San Antonio, San Diego, St. Louis"; note " "; note h=5 justify=left "Cohort 97 (Red line) "; note h=5 justify=left "Atlanta, Jacksonville"; *note h=5 justify=left "Detroit's 1993 and Phoenix '95 '96 ''98 12th grade pop are imputed"; run; quit; /* create 5 panel template, treplay GPLOTs and GSLIDE into SPEC5 template */ /*THIS IS NOT PRINTING TO A WORKING HOLDER. WHY?*/ goptions device=gif GSFNAME=GIFOUT GSFMODE=replace gunit=pct; /*I eliminated reset all from this line and then it started producing graph, but again it stopped working for no reason*/ /*it works if you highlight below individually and run*/ /*I put quit above and then it works*/ Filename GIFOUT "&STORE.Exhibit VII1-3 .gif"; proc greplay nofs igout=work.gseg tc=tempcat; tdef spec5 1/ llx=0 lly=45 ulx=0 uly=90 urx=50 ury=90 lrx=50 lry=45 2/ llx=0 lly=0 ulx=0 uly=45 urx=50 ury=45 lrx=50 lry=0 3/ llx=50 lly=45 ulx=50 uly=90 urx=100 ury=90 lrx=100 lry=45 4/ llx=50 lly=0 ulx=50 uly=45 urx=100 ury=45 lrx=100 lry=0 5/ llx=0 lly=0 ulx=0 uly=100 urx=100 ury=100 lrx=100 lry=0 ; template spec5; *treplay 1:gplot 2:gplot3 3:gplot1 /*4:gplot3*/ 5:gslide; treplay 1:gplot 2:gplot2 3:gplot1 4:gslide2 5:gslide; run; quit; Filename GIFOUT Clear; /* create 5 panel template, treplay GPLOTs and GSLIDE into SPEC5 template */ Filename GIFOUT "&STORE.Exhibit VIII1-3 .gif"; proc greplay nofs igout=work.gseg tc=tempcat; tdef spec5 1/ llx=0 lly=45 ulx=0 uly=90 urx=50 ury=90 lrx=50 lry=45 2/ llx=0 lly=0 ulx=0 uly=45 urx=50 ury=45 lrx=50 lry=0 3/ llx=50 lly=45 ulx=50 uly=90 urx=100 ury=90 lrx=100 lry=45 4/ llx=50 lly=0 ulx=50 uly=45 urx=100 ury=45 lrx=100 lry=0 5/ llx=0 lly=0 ulx=0 uly=100 urx=100 ury=100 lrx=100 lry=0 ; template spec5; treplay 1:gplot3 2:gplot5 3:gplot4 4:gslide2 5:gslide1; run; quit; Filename GIFOUT Clear; ods rtf file="&STORE.Exhibit VII-1 and VIII-1 check .rtf"; proc report data=satact3S2 nowd headline colwidth=8 spacing=1; title "Exhibit VII-1 and VIII-1: Check for Accuracy"; column city cohort_name year total_sattaker total_acttaker total_grade12; define year /order order=data; define cohort_name /order order=data " "; break after year / dol ol ul summarize skip ; run; ODS RTF CLOSE; %macro rep (var=,sub=,taitoru=); ods rtf file="&STORE.&taitoru check .rtf"; proc report data=satact3S2 nowd headline colwidth=8 spacing=1; title "&taitoru : Check for Accuracy"; column cohort_name city year total_&var.&sub. total_&var.taker SM_&var.&sub. weighted_mean; define year /order order=data; define cohort_name /order order=data " "; define total_&var.&sub. /"&var. &sub. score"; define total_&var.taker/"N. of takers" format=comma10.0; define SM_&var.&sub./"&sub. score * N. of takers" format=comma10.0; define weighted_mean / computed; break after year / dol ol ul summarize skip ; compute weighted_mean; weighted_mean=SM_&var.&sub..sum/total_&var.taker.sum; endcomp; run; ODS RTF CLOSE; %mend rep; %rep (taitoru=Exhibit VII-2,var=sat,sub=math); %rep (taitoru=Exhibit VII-3,var=sat,sub=verb); %rep (taitoru=Exhibit VIII-2,var=act,sub=math); %rep (taitoru=Exhibit VIII-3,var=act,sub=sci); /*******************************************************************\ | Rubrics | | | | | | | | | | by Kazuaki Uekawa, Ph.D. (kaz_uekawa@hotmail.com) | \*******************************************************************/ data rubric;set here2.rubric_city; standard_based=mean(of Rubric5 Rubric6 Rubric12 Rubric13 ) ; PD=mean(of Rubric7 rubric8 rubric9 ); Partnership=mean(of rubric10 rubric11 rubric14); if city="Fresno" then Nschl= 93 ; if city="Atlanta" then Nschl= 103 ; if city="St. Louis" then Nschl= 104 ; if city="Phoenix" then Nschl= 120 ; if city="Cleveland" then Nschl= 121 ; if city="New Orleans" then Nschl= 127 ; if city="Columbus" then Nschl= 134 ; if city="Jacksonville" then Nschl= 154 ; if city="Milwaukee" then Nschl= 155 ; if city="Memphis " then Nschl= 160 ; if city="El Paso" then Nschl= 166 ; if city="San Diego" then Nschl= 178 ; if city="Baltimore" then Nschl= 187 ; if city="Dallas" then Nschl= 217 ; if city="Philadelphia " then Nschl= 259 ; if city="Detroit" then Nschl= 260 ; if city="Miami " then Nschl= 284 ; if city="San Antonio" then Nschl= 290 ; if city="Houston" then Nschl= 295 ; if city="Chicago" then Nschl= 534 ; if city="Los Angeles" then Nschl= 570 ; if city="New York" then Nschl= 1145 ; if city="St. Louis" then stdsize= 39047 ; if city="Atlanta" then stdsize= 54320 ; if city="Columbus" then stdsize= 62481 ; if city="Cleveland" then stdsize= 71431 ; if city="Fresno" then stdsize= 78520 ; if city="New Orleans" then stdsize= 82288 ; if city="Phoenix" then stdsize= 84008 ; if city="Baltimore" then stdsize= 94763 ; if city="Milwaukee" then stdsize= 103777 ; if city="Memphis" then stdsize= 109931 ; if city="Jacksonville" then stdsize= 123261 ; if city="El Paso" then stdsize= 135677 ; if city="San Diego" then stdsize= 138356 ; if city="Dallas " then stdsize= 153404 ; if city="Detroit" then stdsize= 184139 ; if city="Philadelphia " then stdsize= 201425 ; if city="Houston" then stdsize= 208000 ; if city="San Antonio" then stdsize= 230449 ; if city="Miami " then stdsize= 359021 ; if city="Chicago" then stdsize= 411859 ; if city="Los Angeles" then stdsize= 592975 ; if city="New York" then stdsize= 1099437 ; /*get actual year data is about... varies depeding on cohort*/ if city= 'Hypothetical' or city='Chicago' or city='Baltimore' or city='Dallas' or city='Detroit' or city='El Paso' or city='Miami' or city='New York' or city='Phoenix' then do; /*give various cohort names for later convinience*/ cohort=1; cohort2=93; cohort_name="Cohort 93"; end; if city='Cleveland' or city='Columbus' or city='Fresno' or city='Los Angeles' or city='Memphis' or city='New Orleans' or city='Philadelphia' then do; cohort=2; cohort2=94; cohort_name="Cohort 94"; end; if city='Milwaukee' or city= 'St. Louis' or city= 'San Antonio' or city= 'San Diego' then do; cohort=3; cohort2=95; cohort_name="Cohort 95"; end; if city='Atlanta' or city='Jacksonville' then do; cohort=4; cohort2=97; cohort_name="Cohort 97"; end; if city='Houston' then do; cohort=5; cohort2=99; cohort_name="Cohort 99"; end; run; /*******************************************************************\ | Relation Among Subgroups of Rubric Items | | | | | | | | | | by Kazuaki Uekawa, Ph.D. (kaz_uekawa@hotmail.com) | \*******************************************************************/ goptions reset=all; /* set max, min, and tick numbers for X,Y,Z axes */ %let x_min=0; %let x_max=1; %let x_ticks=4; %let y_min=0; %let y_max=1; %let y_ticks=4; %let z_min=0; %let z_max=1; %let z_ticks=4; /* create REV format */ proc format; picture rev low - < 0 = '00009.00' 0 < - high = '00009.00' (prefix='-'); run; proc rank data=rubric out=rubric2 groups=3; var stdsize; ranks student_pop; run; data rubric4;set rubric2; length student_pop2 $8; if student_pop=0 then do; student_pop2="Small"; sizeval=1; end; if student_pop=1 then do; student_pop2="Medium"; sizeval=2; end; if student_pop=2 then do; student_pop2="Large"; sizeval=3; end; if city="Chicago" then state= "IL"; if city="Atlanta" then state= "GA"; if city="Baltimore" then state= "MD"; if city="Cleveland" then state= "OH"; if city="Columbus" then state= "OH"; if city="Dallas" then state= "TX"; if city="Detroit" then state= "MI"; if city="El Paso" then state= "TX"; if city="Fresno" then state= "CA"; if city="Houston" then state= "TX"; if city="Jacksonville " then state= "FL"; if city="Los Angeles " then state= "CA"; if city="Memphis" then state= "TN"; if city="Miami" then state= "FL"; if city="Milwaukee" then state= "WI"; if city="New Orleans" then state= "LA"; if city="New York" then state= "NY"; if city="Philadelphia" then state= "PA"; if city="Phoenix" then state= "AZ"; if city="San Antonio" then state= "TX"; if city="San Diego" then state= "CA"; if city="St. Louis" then state= "MO"; if city="Milwaukee" then city2= "MIL"; if city="Chicago" then city2= "CH"; if city="Atlanta" then city2= "AT"; if city="Baltimore" then city2= "BA"; if city="Cleveland" then city2= "CL"; if city="Columbus" then city2= "CO"; if city="Dallas" then city2= "DA"; if city="Detroit" then city2= "DE"; if city="El Paso" then city2= "EP"; if city="Fresno" then city2= "FR"; if city="Houston" then city2= "HO"; if city="Jacksonville " then city2= "JA"; if city="Los Angeles " then city2= "LA"; if city="Memphis" then city2= "ME"; if city="Miami" then city2= "MIA"; if city="New Orleans" then city2= "NO"; if city="New York" then city2= "NY"; if city="Philadelphia" then city2= "PHI"; if city="Phoenix" then city2= "PHO"; if city="San Antonio" then city2= "SA"; if city="San Diego" then city2= "SD"; if city="St. Louis" then city2= "SL"; %macro mice (var1,var2,var3,lab1,lab2,lab3,taitoru1,taitoru2,taitoru3); proc sort data=rubric4 out=rubric5; by &var1 &var2; run; /* add small amount to duplicate X and Y values */ data modify; set rubric5; by &var1 &var2; if ^first.&var1 and ^first.&var2 then &var2=.00001+&var2; run; /* Create data set, THREE */ data three; length colorval shapeval $8; set modify; if cohort=1 then do; shapeval='balloon'; colorval='purple'; end; if cohort=2 then do; shapeval='balloon'; colorval='green'; end; if cohort=3 then do; shapeval='balloon'; colorval='blue'; end; if cohort=4 then do; shapeval='balloon'; colorval='red'; end; flag="A"; run; data four; set three end=last; output; if last; /* Create two 'dummy' observations with the min and max x, y and z values */ &var2=&x_min; &var1=&y_min; &var3=&z_min; colorval='white'; shapeval='point'; /* 'Hide' the 'dummy' points */ output; xvar=&x_max; yvar=&y_max; zvar=&z_min; colorval='white'; shapeval='point'; /* 'Hide' the 'dummy' points */ output; run; /* reverse Y-axis values */ data five; set four; &var1=-1*&var1; /* multipled &y variable by -1 to create newlabel.sas */ %include "&WD2.newlabel.sas"; *%include "c:\newlabel.sas"; %label(data=three, x=&var2, y=&var1,z=&var3, color='black', size=1.2, /* subset=origin='A' and &var2 >10000*/ subset=1, pos=1, text=city2/*scan(city,1)*/ ); goptions reset=all device=gif GSFNAME=GIFOUT GSFMODE=replace gunit=pct cback=white /* htitle=3*/ htext=2.5/*ftext=swissb ctext=blue*/ /*vsize=10 hsize=8*/; proc greplay nofs igout=work.gseg;delete _all_;run; Filename GIFOUT "&STORE.&taitoru1 .gif"; proc G3D data=five; title1 "&taitoru1" ; title2 &taitoru2; title3 &taitoru3; footnote1 h=2 justify=left "NOTES:"; footnote2 h=2 justify=left "The size of the bubbles represents the number of students enrolled"; footnote3 justify=left color=purple h=2 "Cohort 93: Baltimore(BA), Chicago(CH), Dallas(DA), Detroit(DE), El Paso(EP), Miami(MIA), New York(NY), Phoenix(PHO) "; footnote4 justify=left color=green h=2 "Cohort 94: Cleveland(CL), Columbus(CO), Fresno(FR), LA(LA), Memphis(MEM), New Orleans(NO), Philadelphia(PHI)"; footnote5 justify=left color=blue h=2 "Cohort 95: Milwaukee(MIL), San Antonio(SA), San Diego(SD), St. Louis(SL)"; footnote6 justify=left color=red h=2 "Cohort 96: Atlanta(AT), Jacksonville(JA)"; /* generate angled z-axis label */ note a=90 m=(5,40)pct f=swissb &lab3; scatter &var1*&var2=&var3/ annotate=_label_ shape=shapeval color=colorval size=sizeval xticknum=&x_ticks yticknum=&y_ticks zticknum=&z_ticks; label &var1=&lab1 &var2=&lab2 &var3="00"x; /* suppress default z-axis label */ format &var1 rev.; /* assign REV format for Y-axis variable */ run; Filename GIFOUT Clear; *%macro baka1; ods rtf file="&STORE.&taitoru1..rtf" /* style=minimal*/; proc report data=rubric nowd headline colwidth=8 spacing=1; title4 "RAW DATA"; column city &var1 &var2 &var3; define city /"Cities"; define &var1 /&lab1; define &var2 /&lab2; define &var3 /&lab3; run; title4 ; ODS RTF CLOSE; *%mend; %mend mice; %mice (var1=rubric1,var2=rubric2,var3=rubric3, lab1="Rubric1", lab2="Rubric2", lab3="Rubric3", /* lab1="Equal Access", lab2="Student Support Programs", lab3="Graduation and Promotion Policy",*/ taitoru1= Exhibit XII-1,taitoru2="Equal Access, Student Support Programs, Graduation and Promotion Policy"); %mice (var1=rubric5,var2=rubric6,var3=rubric12, lab1="Rubric5", lab2="Rubric6", lab3="Rubric12", /* lab1="Standard-based Curriculum", lab2="Assessment and M/S Instructional Time", lab3="Assessment",*/ taitoru1= Exhibit XII-2,taitoru2="Standard-based Curriculum, Assessment and M/S Instructional Time, Assessment"); %mice (var1=rubric7,var2=rubric8,var3=rubric9, lab1="Rubric7", lab2="Rubric8", lab3="Rubric9", /*lab1="Teacher Qualification", lab2="PD (Knowledge & Alignment)", lab3="PD (Participation & Evaluation)",*/ taitoru1=Exhibit XII-3,taitoru2="Teacher Qualification, PD (Knowledge & Alignment), PD (Participation & Evaluation)"); %mice (var1=rubric10,var2=rubric11,var3=rubric14, lab1="Rubric10", lab2="Rubric11", lab3="Rubric14", /* lab1="Leadership, Governance & Management", lab2="Collaboration, Partnership" lab3="Coordination, Leverage of Resources & Use of Data and Technology",*/ taitoru1= Exhibit XII-4, taitoru2="Leadership, Governance, & Management; Collaboration, Partnership;", taitoru3=" Coordination, Leverage of Resource, & Use of Data & Technology"); %mice (var1=standard_based,var2=PD,var3=partnership, lab1="Standard-based Instruction", lab2="PD", lab3="Partnership", taitoru1= Exhibit XII-5,taitoru2="USI Districts by 3 Subgroups of Rubric Items", taitoru3="Standards-based Instruction, Partnership, Professional Development" ); /*here2 CHECK ACCURACY OF RUBRIC VARIABLES*/ ods rtf file="&STORE.Exhibit XII1-5..rtf" /* style=minimal*/; proc report data=rubric nowd headline colwidth=8 spacing=1; title1 "Exhibit XII1-5"; title4 "Rubric 1: CHECK FOR ACCURACY"; column city r1_1ana r1_1linda r1_1greta rubric1_1 r1_2ana r1_2linda r1_2greta rubric1_2 rubric1; define city /"Cities"; *define &var1 /&lab1; *define &var2 /&lab2; *define &var3 /&lab3; run; *title4 ; proc report data=rubric nowd headline colwidth=8 spacing=1; title1 "Exhibit XII1-5"; title4 "Rubric2: CHECK FOR ACCURACY"; column city r2_1ana r2_1linda r2_1greta rubric2_1 r2_2ana r2_2linda r2_2greta rubric2_2 rubric2; define city /"Cities"; *define &var1 /&lab1; *define &var2 /&lab2; *define &var3 /&lab3; run; proc report data=rubric nowd headline colwidth=4 spacing=2; title1 "Exhibit XII1-5"; title4 "Rubric3: CHECK FOR ACCURACY"; column city r3_1ana r3_1linda r3_1greta rubric3_1 r3_2ana r3_2linda r3_2greta rubric3_2 r3_3ana r3_3linda r3_3greta rubric3_3 rubric3; define city /"Cities"; *define &var1 /&lab1; *define &var2 /&lab2; *define &var3 /&lab3; run; proc report data=rubric nowd headline colwidth=4 spacing=2; title1 "Exhibit XII1-5"; title4 "Rubric4: CHECK FOR ACCURACY"; column city r4_1ana r4_1linda r4_1greta rubric4_1 r4_2ana r4_2linda r4_2greta rubric4_2 r4_3ana r4_3linda r4_3greta rubric4_3 rubric4; define city /"Cities"; *define &var1 /&lab1; *define &var2 /&lab2; *define &var3 /&lab3; run; proc report data=rubric nowd headline colwidth=4 spacing=2; title1 "Exhibit XII1-5"; title4 "Rubric5: CHECK FOR ACCURACY"; column city r5_1ana r5_1linda r5_1greta rubric5_1 r5_2ana r5_2linda r5_2greta rubric5_2 r5_3ana r5_3linda r5_3greta rubric5_3 rubric5; define city /"Cities"; *define &var1 /&lab1; *define &var2 /&lab2; *define &var3 /&lab3; run; proc report data=rubric nowd headline colwidth=8 spacing=1; title1 "Exhibit XII1-5"; title4 "Rubric6: CHECK FOR ACCURACY"; column city r6_1ana r6_1linda r6_1greta rubric6_1 r6_2ana r6_2linda r6_2greta rubric6_2 rubric6; define city /"Cities"; *define &var1 /&lab1; *define &var6 /&lab2; *define &var3 /&lab3; run; %let suji=7; /*for 3-item rubrics*/ proc report data=rubric nowd headline colwidth=4 spacing=2; title1 "Exhibit XII1-5"; title4 "Rubric&suji: CHECK FOR ACCURACY"; column city r&suji._1ana r&suji._1linda r&suji._1greta rubric&suji._1 r&suji._2ana r&suji._2linda r&suji._2greta rubric&suji._2 r&suji._3ana r&suji._3linda r&suji._3greta rubric&suji._3 rubric&suji; define city /"Cities"; *define rr&var1 /rr&lab1; *define rr&var2 /rr&lab2; *define rr&var3 /rr&lab3; run; %let suji=8; /*for 3-item rubrics*/ proc report data=rubric nowd headline colwidth=4 spacing=2; title1 "Exhibit XII1-5"; title4 "Rubric&suji: CHECK FOR ACCURACY"; column city r&suji._1ana r&suji._1linda r&suji._1greta rubric&suji._1 r&suji._2ana r&suji._2linda r&suji._2greta rubric&suji._2 r&suji._3ana r&suji._3linda r&suji._3greta rubric&suji._3 r&suji._4ana r&suji._4linda r&suji._4greta rubric&suji._4 rubric&suji; define city /"Cities"; *define rr&var1 /rr&lab1; *define rr&var2 /rr&lab2; *define rr&var3 /rr&lab3; run; %let suji=9; /*for 3-item rubrics*/ proc report data=rubric nowd headline colwidth=4 spacing=2; title1 "Exhibit XII1-5"; title4 "Rubric&suji: CHECK FOR ACCURACY"; column city r&suji._1ana r&suji._1linda r&suji._1greta rubric&suji._1 r&suji._2ana r&suji._2linda r&suji._2greta rubric&suji._2 r&suji._3ana r&suji._3linda r&suji._3greta rubric&suji._3 r&suji._4ana r&suji._4linda r&suji._4greta rubric&suji._4 rubric&suji; define city /"Cities"; *define rr&var1 /rr&lab1; *define rr&var2 /rr&lab2; *define rr&var3 /rr&lab3; run; %let suji=10; /*for 3-item rubrics*/ proc report data=rubric nowd headline colwidth=4 spacing=2; title1 "Exhibit XII1-5"; title4 "Rubric&suji: CHECK FOR ACCURACY"; column city r&suji._1ana r&suji._1linda r&suji._1greta rubric&suji._1 r&suji._2ana r&suji._2linda r&suji._2greta rubric&suji._2 r&suji._3ana r&suji._3linda r&suji._3greta rubric&suji._3 rubric&suji; define city /"Cities"; *define rr&var1 /rr&lab1; *define rr&var2 /rr&lab2; *define rr&var3 /rr&lab3; run; %let suji=11; /*for 3-item rubrics*/ proc report data=rubric nowd headline colwidth=4 spacing=2; title1 "Exhibit XII1-5"; title4 "Rubric&suji: CHECK FOR ACCURACY"; column city r&suji._1ana r&suji._1linda r&suji._1greta rubric&suji._1 r&suji._2ana r&suji._2linda r&suji._2greta rubric&suji._2 r&suji._3ana r&suji._3linda r&suji._3greta rubric&suji._3 r&suji._4ana r&suji._4linda r&suji._4greta rubric&suji._4 r&suji._5ana r&suji._5linda r&suji._5greta rubric&suji._5 rubric&suji; define city /"Cities"; *define rr&var1 /rr&lab1; *define rr&var2 /rr&lab2; *define rr&var3 /rr&lab3; run; %let suji=12; /*for 3-item rubrics*/ proc report data=rubric nowd headline colwidth=4 spacing=2; title1 "Exhibit XII1-5"; title4 "Rubric&suji: CHECK FOR ACCURACY"; column city r&suji._1ana r&suji._1linda r&suji._1greta rubric&suji._1 r&suji._2ana r&suji._2linda r&suji._2greta rubric&suji._2 r&suji._3ana r&suji._3linda r&suji._3greta rubric&suji._3 r&suji._4ana r&suji._4linda r&suji._4greta rubric&suji._4 r&suji._5ana r&suji._5linda r&suji._5greta rubric&suji._5 rubric&suji; define city /"Cities"; *define rr&var1 /rr&lab1; *define rr&var2 /rr&lab2; *define rr&var3 /rr&lab3; run; %let suji=13; /*for 3-item rubrics*/ proc report data=rubric nowd headline colwidth=4 spacing=2; title1 "Exhibit XII1-5"; title4 "Rubric&suji: CHECK FOR ACCURACY"; column city r&suji._1ana r&suji._1linda r&suji._1greta rubric&suji._1 r&suji._2ana r&suji._2linda r&suji._2greta rubric&suji._2 r&suji._3ana r&suji._3linda r&suji._3greta rubric&suji._3 rubric&suji; define city /"Cities"; *define rr&var1 /rr&lab1; *define rr&var2 /rr&lab2; *define rr&var3 /rr&lab3; run; %let suji=14; /*for 3-item rubrics*/ proc report data=rubric nowd headline colwidth=4 spacing=2; title1 "Exhibit XII1-5"; title4 "Rubric&suji: CHECK FOR ACCURACY"; column city r&suji._1ana r&suji._1linda r&suji._1greta rubric&suji._1 r&suji._2ana r&suji._2linda r&suji._2greta rubric&suji._2 r&suji._3ana r&suji._3linda r&suji._3greta rubric&suji._3 r&suji._4ana r&suji._4linda r&suji._4greta rubric&suji._4 rubric&suji; define city /"Cities"; *define rr&var1 /rr&lab1; *define rr&var2 /rr&lab2; *define rr&var3 /rr&lab3; run; ODS RTF CLOSE; /*CREATING RADAR GRAPHS*/ /*******************************************************************\ | Radar graphs for Rubric Items | | Prepping data | | | | | | | | by Kazuaki Uekawa, Ph.D. (kaz_uekawa@hotmail.com) | \*******************************************************************/ proc rank data=rubric out=bothR groups=3; var stdsize nschl; ranks student_pop Rnschl; run; data bothR;set bothR; if student_pop=1 then student_pop2="Midium"; if student_pop=0 then student_pop2="Small"; if student_pop=2 then student_pop2="Large"; %macro john (cohort2=); proc sort data=bothR;by &cohort2;run; proc means data=bothR noprint; by &cohort2; output out=bothmean mean=; var Rubric5 Rubric6 Rubric12 Rubric13 Rubric7 rubric8 rubric9 rubric10 rubric11 rubric14 ; run; proc transpose data=bothmean out=bothmean2; by &cohort2; run; data &cohort2;set bothmean2; keep &cohort2 rubric_type groups value; value=col1; rubric_type=_name_; if rubric_type="Rubric5" then groups="Standard-based"; if rubric_type="Rubric6" then groups="Standard-based"; if rubric_type="Rubric12" then groups="Standard-based"; if rubric_type="Rubric13" then groups="Standard-based"; if rubric_type="Rubric7" then groups="PD"; if rubric_type="Rubric8" then groups="PD"; if rubric_type="Rubric9" then groups="PD"; if rubric_type="Rubric10" then groups="Partnership"; if rubric_type="Rubric11" then groups="Partnership"; if rubric_type="Rubric14" then groups="Partnership"; if rubric_type ne "_TYPE_"; if rubric_type ne "_FREQ_"; %mend john; %john (cohort2=cohort2); %john (cohort2=student_pop2); /*******************************************************************\ | Radar graphs | 1. by cohort | 2. by Size of a school district | | | | | | | | by Kazuaki Uekawa, Ph.D. (kaz_uekawa@hotmail.com) | \*******************************************************************/ %macro mac1 (student_pop2=,name=,taitoru=); footnote; title1; title2; title3; proc sort data=&student_pop2;by groups;run; *goptions GSFNAME=GIFOUT GSFMODE=replace display hsize=0 htext=5 gunit=pct cback=white; proc greplay nofs igout=work.gseg;delete _all_;run; goptions vsize=5 hsize=3.75 nodisplay htext=5 GSFNAME=GIFOUT GSFMODE=replace gunit=pct cback=white ; *options GSFNAME=GIFOUT GSFMODE=replace display hsize=0 htext=5 gunit=pct cback=white; proc gradar data=&student_pop2; title h=3.5 "Professional Development Rubrics"; where groups="PD"; chart rubric_type/sumvar=value overlay=&student_pop2 starcircles=( 0 0.5 1.0) starcircle=1 cstarfill=( lib vlib mob dab); run; proc gradar data=&student_pop2; title h=3.5 "Partnership Rubrics"; where groups="Partnership"; chart rubric_type/sumvar=value overlay=&student_pop2 starcircles=( 0 0.5 1.0) starcircle=1 cstarfill=( lib vlib mob dab) ;run; proc gradar data=&student_pop2; title h=3.5 "Standard-based Rubrics"; where groups="Standard-based"; chart rubric_type/sumvar=value overlay=&student_pop2 starcircles=( 0 0.5 1.0) /*cstars=red cframe=ltgray*/starcircle=1 cstarfill=( lib vlib mob dab) /* starfill=(solid solid) */ /*acrossvar=groups*/ /*available only SAS version 8.2 staraxis=(axis1,axis2)*/ ;run; quit; *goptions vsize=0 hsize=0; proc gslide ; title1 h=5 "Notes"; note h=5 "Professional Development Rubrics"; note h=5 "R7 Teacher Qualifications"; note h=5 "R8 PD: Content Knowledge & Alignment "; note h=5 "with Standards"; note h=5 "R9 PD Participation & Evaluation"; note " "; note h=5 "Partnership Rubrics"; note h=5 "R10 Leadership, Governance, & Management "; note h=5 "R11 Collaboration, Partnerships with Parents,Higher Education"; note h=5 "Business and Partners for Students"; note h=5 "R14 Coordination, Leverage of Resources, "; note h=5 "& Use of Data & Technology "; note " "; note h=5 "Standard-based Rubrics"; note h=5 "R12 Assessment"; note h=5 "R13 Accountability & Use of District Data"; note h=5 "R5 Standards-based Curriculum"; note h=5 "R6 Assessment & M/S Instructional Time"; note " "; run; /*back to default*/ goptions vsize=0 hsize=0; proc gslide ; title1 h=3 "&name "; title2 h=3 "&taitoru"; *title3 h=3 "&taitoru2"; run; quit; /*turn display on*/ goptions display; /* create 5 panel template, treplay GPLOTs and GSLIDE into SPEC5 template */ goptions GSFNAME=GIFOUT GSFMODE=replace display hsize=0 htext=5 gunit=pct cback=white; Filename GIFOUT "&STORE.&name .gif"; proc greplay nofs igout=work.gseg tc=tempcat; tdef spec5 1/ llx=0 lly=45 ulx=0 uly=90 urx=50 ury=90 lrx=50 lry=45 2/ llx=0 lly=0 ulx=0 uly=45 urx=50 ury=45 lrx=50 lry=0 3/ llx=50 lly=45 ulx=50 uly=90 urx=100 ury=90 lrx=100 lry=45 4/ llx=50 lly=0 ulx=50 uly=45 urx=100 ury=45 lrx=100 lry=0 5/ llx=0 lly=0 ulx=0 uly=100 urx=100 ury=100 lrx=100 lry=0 ; template spec5; treplay 1:radar 2:radar1 3:radar2 4:gslide 5:gslide1; run; Filename GIFOUT Clear; quit; %mend mac1; %mac1 (name=Exhibit XIII-1, student_pop2=cohort2, taitoru=Rubrics by Cohort); %mac1 (name=Exhibit XIII-2, student_pop2=student_pop2,taitoru=Rubrics by Size of School Districts); ods rtf file="&STORE.Exhibit XIII-1.rtf" /* style=minimal*/; *%let student_pop2=student_pop2; *%let student_pop2=cohort_name; %let student_pop2=cohort2; proc report data=&student_pop2 nowd headline colwidth=5 spacing=1; title1 "Exhibit XIII-1"; title2 "Rubrics by cohort"; column groups &student_pop2 rubric_type value; define groups /"item subgroup"; define student_pop2 /"cohort"; define value / format=comma8.3; run; *%let student_pop2=student_pop2; *%let student_pop2=cohort2; proc report data=bothr nowd headline colwidth=5 spacing=1; title3 "PD items: Accuracy Check"; column &student_pop2 city cohort_name rubric7 rubric8 rubric9 ; define &student_pop2 /order order=data ; define rubric7/ format=percent8.2 mean; define rubric8/ format=percent8.2 mean; define rubric9/ format=percent8.2 mean; *define PD /format=percent8.2; *define standard_based /format=percent8.2; *define partnership/format=percent8.2; break after &student_pop2 / dol summarize skip ; run; proc report data=bothr nowd headline colwidth=5 spacing=1; title3 "Standard_based items: Accuracy Check"; column &student_pop2 city cohort_name rubric10 rubric11 rubric14 ; define &student_pop2 /order order=data ; *define PD /format=percent8.2; *define standard_based /format=percent8.2; *define partnership/format=percent8.2; define rubric10/ format=percent8.2 mean; define rubric11/ format=percent8.2 mean; define rubric14/ format=percent8.2 mean; break after &student_pop2 / dol summarize skip ; run; proc report data=bothr nowd headline colwidth=5 spacing=1; title3 "Partnership Items: Accuracy Check"; column &student_pop2 city cohort_name rubric5 rubric6 rubric12 rubric13 ; define &student_pop2 /order order=data ; define rubric5/ format=percent8.2 mean; define rubric6/ format=percent8.2 mean; define rubric12/ format=percent8.2 mean; define rubric13/ format=percent8.2 mean; *define PD /format=percent8.2; *define standard_based /format=percent8.2; *define partnership/format=percent8.2; break after &student_pop2 / dol summarize skip ; run; ods rtf close; ods rtf file="&STORE.Exhibit XIII-2.rtf" /* style=minimal*/; %let student_pop2=student_pop2; *%let student_pop2=cohort2; proc report data=&student_pop2 nowd headline colwidth=5 spacing=1; title1 "Exhibit XIII-2"; title2 "Rubrics by Size of School Districts"; title3 "Raw Data"; column groups &student_pop2 rubric_type value; define groups /"item subgroup"; define student_pop2 /"cohort"; define value / format=comma8.3; run; *%let student_pop2=student_pop2; *%let student_pop2=cohort2; proc report data=bothr nowd headline colwidth=5 spacing=1; title3 "PD items: Accuracy Check"; column &student_pop2 city cohort_name rubric7 rubric8 rubric9 ; define &student_pop2 /order order=data ; define rubric7/ format=percent8.2 mean; define rubric8/ format=percent8.2 mean; define rubric9/ format=percent8.2 mean; *define PD /format=percent8.2; *define standard_based /format=percent8.2; *define partnership/format=percent8.2; break after &student_pop2 / dol summarize skip ; run; proc report data=bothr nowd headline colwidth=5 spacing=1; title3 "Standard_based items: Accuracy Check"; column &student_pop2 city cohort_name rubric10 rubric11 rubric14 PD ; define &student_pop2 /order order=data ; *define PD /format=percent8.2; *define standard_based /format=percent8.2; *define partnership/format=percent8.2; define rubric10/ format=percent8.2 mean; define rubric11/ format=percent8.2 mean; define rubric14/ format=percent8.2 mean; break after &student_pop2 / dol summarize skip ; run; proc report data=bothr nowd headline colwidth=5 spacing=1; title3 "Partnership Items: Accuracy Check"; column &student_pop2 city cohort_name rubric5 rubric6 rubric12 rubric13 ; define &student_pop2 /order order=data ; define rubric5/ format=percent8.2 mean; define rubric6/ format=percent8.2 mean; define rubric12/ format=percent8.2 mean; define rubric13/ format=percent8.2 mean; *define PD /format=percent8.2; *define standard_based /format=percent8.2; *define partnership/format=percent8.2; break after &student_pop2 / dol summarize skip ; run; ods rtf close; *%macro kaza2; *%mend; /*******************************************************************\ | Vivariate plots | | Between rubric items vs. outcome variables | | Prepping data | | | | | | by Kazuaki Uekawa, Ph.D. (kaz_uekawa@hotmail.com) | \*******************************************************************/ /*FIRST MERGE DATA SETS*/ data enrollment;length city $ 13;set here2.enrollment_City; *city=compress(trim(city)); *if city ne "New Orleans";/*NO's data has an error, so removed from analysis*/ drop cohort; run; proc sort;by city;run; data sat_act;length city $ 13;set here2.sat_act_city; *city=compress(trim(city)); if city= "Miami-Dade" then city="Miami"; drop cohort; proc sort;by city;run; data ap;length city $ 13;set here2.ap_city; *city=compress(trim(city)); if city= "Miami-Dade" then city="Miami"; if city ne "Miami-Dade"; drop cohort; proc sort;by city;run; *proc print data=ap; *run; /*Must make AP city data data rubric;length city $ 13; set here2.rubric_city; *city=compress(trim(city)); drop cohort; proc sort;by city;run; */ proc sort data=rubric ;by city;run; data all;merge enrollment sat_act rubric ap;by city; if city ne "Hypothetical"; /*create weights*/ flag=1; standard_based=mean(of Rubric5 Rubric6 Rubric12 Rubric13 ) ; PD=mean(of Rubric7 rubric8 rubric9 ); Partnership=mean(of rubric10 rubric11 rubric14); if city="Fresno" then Nschl= 93 ;if city="Atlanta" then Nschl= 103 ;if city="St. Louis" then Nschl= 104 ;if city="Phoenix" then Nschl= 120 ; if city="Cleveland" then Nschl= 121 ;if city="New Orleans" then Nschl= 127 ;if city="Columbus" then Nschl= 134 ;if city="Jacksonville" then Nschl= 154 ; if city="Milwaukee" then Nschl= 155 ;if city="Memphis " then Nschl= 160 ;if city="El Paso" then Nschl= 166 ;if city="San Diego" then Nschl= 178 ; if city="Baltimore" then Nschl= 187 ;if city="Dallas" then Nschl= 217 ;if city="Philadelphia " then Nschl= 259 ;if city="Detroit" then Nschl= 260 ; if city="Miami " then Nschl= 284 ;if city="San Antonio" then Nschl= 290 ;if city="Houston" then Nschl= 295 ;if city="Chicago" then Nschl= 534 ; if city="Los Angeles" then Nschl= 570 ;if city="New York" then Nschl= 1145 ;if city="St. Louis" then stdsize= 39047 ;if city="Atlanta" then stdsize= 54320 ; if city="Columbus" then stdsize= 62481 ;if city="Cleveland" then stdsize= 71431 ;if city="Fresno" then stdsize= 78520 ;if city="New Orleans" then stdsize= 82288 ; if city="Phoenix" then stdsize= 84008 ;if city="Baltimore" then stdsize= 94763 ;if city="Milwaukee" then stdsize= 103777 ;if city="Memphis" then stdsize= 109931 ; if city="Jacksonville" then stdsize= 123261 ;if city="El Paso" then stdsize= 135677 ;if city="San Diego" then stdsize= 138356 ; if city="Dallas " then stdsize= 153404 ;if city="Detroit" then stdsize= 184139 ;if city="Philadelphia " then stdsize= 201425 ; if city="Houston" then stdsize= 208000 ;if city="San Antonio" then stdsize= 230449 ;if city="Miami " then stdsize= 359021 ; if city="Chicago" then stdsize= 411859 ;if city="Los Angeles" then stdsize= 592975 ;if city="New York" then stdsize= 1099437 ; /*get actual year data is about... varies depeding on cohort*/ if city= 'Hypothetical' or city='Chicago' or city='Baltimore' or city='Dallas' or city='Detroit' or city='El Paso' or city='Miami' or city='New York' or city='Phoenix' then do;/*give various cohort names for later convinience*/cohort=1;cohort2=93;cohort_name="Cohort 93";end; if city='Cleveland' or city='Columbus' or city='Fresno' or city='Los Angeles' or city='Memphis' or city='New Orleans' or city='Philadelphia' then do; cohort=2; cohort2=94;cohort_name="Cohort 94";end; if city='Milwaukee' or city= 'St. Louis' or city= 'San Antonio' or city= 'San Diego' then do;cohort=3;cohort2=95;cohort_name="Cohort 95";end; if city='Atlanta' or city='Jacksonville' then do;cohort=4;cohort2=97;cohort_name="Cohort 97";end; if city='Houston' then do;cohort=5;cohort2=99;cohort_name="Cohort 99";end; /*here2 Create SELECT variables*/ /*Selection of Cities*/ /*See Ana's Teleconference Notes Jan 9,2002*/ use_alge1=0; if city = "Miami" or city="Columbus" or city="Fresno" or city="Los Angeles" or city="Memphis" or city="Philadelphia" or city="San Antonio" or city="San Diego" or city="Atlanta" or city="Jacksonville" then use_alge1=1; use_himath=0; if city="Chicago" or city="Miami" or city="New York" or city="Cleveland" or city="Columbus" or city="Fresno" or city="Los Angeles" or city="Memphis" or city="Philadelphia" or city="San Antonio" or city="San Diego" or city="St. Louise" or city="Atlanta" or city="Jacksonville" then use_himath=1; use_allsci=0; if city="Chicago" or city="Miami" or city="New York" or city="Cleveland" or city="Columbus" or city="Fresno" or city="Los Angeles" or city="Memphis" or city="Philadelphia" or city="San Antonio" or city="San Diego" or city="St. Louis" or city="Atlanta" or city="Jacksonville" then use_allsci=1; use_all=1; /*Decided that these two cities should not be in the scatter plots*/ /*Feb 2002*/ if city="Atlanta" or city="Jacksonville" then eliminate=1; if eliminate ne 1; *proc print data=all; *var city cohort length;*run; run; %macro asdf2 (var1); proc means data=all noprint sum; where &var1 > -9 and length >-9; var &var1 length; output out=&var1 (keep=_FREQ_ length) sum=; run; data &var1 ; set &var1; keep &var1.seed &var1.freq &var1.length; &var1.seed=_freq_/length; &var1.freq=_freq_; &var1.length=length; %mend asdf2; %asdf2 (var1=Rubric1); %asdf2 (var1=Rubric1_1); %asdf2 (var1=Rubric1_2); %asdf2 (var1=Rubric3); %asdf2 (var1=Rubric3_1); %asdf2 (var1=Rubric3_2); %asdf2 (var1=Rubric1and3); %asdf2 (var1=Rubric2); %asdf2 (var1=Rubric2_1); %asdf2 (var1=Rubric2_2); %asdf2 (var1=Rubric4); %asdf2 (var1=Rubric2and4); %asdf2 (var1=Rubric8and9); %asdf2 (var1=Rubric7); data seeds;merge Rubric1 Rubric1_1 Rubric1_2 Rubric3 Rubric3_1 Rubric3_2 Rubric1and3 Rubric2 Rubric2_1 Rubric2_2 Rubric4 Rubric2and4 Rubric8and9 Rubric7 ; flag=1; /*start from here2*/ data all;merge all seeds;by flag; %macro toyota (ruby); if &ruby > -9 then do; weight&ruby=length*&ruby.seed; end; W_&ruby=&ruby*length*&ruby.seed; %mend toyota; %toyota (ruby=Rubric1); %toyota (ruby=Rubric1_1); %toyota (ruby=Rubric1_2); %toyota (ruby=Rubric3); %toyota (ruby=Rubric3_1); %toyota (ruby=Rubric3_2); %toyota (ruby=Rubric1and3); %toyota (ruby=Rubric2); %toyota (ruby=Rubric2_1); %toyota (ruby=Rubric2_2); %toyota (ruby=Rubric4); %toyota (ruby=Rubric2and4); %toyota (ruby=Rubric8and9); %toyota (ruby=Rubric7); proc print data=all; var city rubric1 length rubric1seed weightrubric1 w_rubric1 rubric8and9;run; %macro for_graph (ID=,flag=,select=,outcome=,factor=,name=,taitoru1=,taitoru2=,taitoru3=,h_label=,v_label=); goptions reset=global GSFNAME=GIFOUT GSFMODE=replace display gunit=pct cback=white colors=(black blue green red) htitle=5 htext=3 ftext=zapf border dev=gif ; data all2;set all; keep city city2 &outcome &factor stdsize color cohort_name Nocleveland flag; color=" "; if cohort2=93 then color="*"; if cohort2=94 then color="#"; if cohort2=95 then color="+"; if cohort2=97 then color="^"; NoCleveland=1; if city="Cleveland" then NoCleveland=0;/*to get rid of cleveland from X-1s tables*/ flag=1; city2=compress(color||city); if use_&select = 1; Filename GIFOUT "&STORE.&taitoru1..gif"; title1 height=2.5 pct "&taitoru1"; title2 height=2.5 pct "&taitoru2"; title3 height=2.5 pct "Versus &taitoru3"; title4 height=2 pct "Weighted by Time Factor"; footnote1 height=2 "*=Cohort93, #=Cohort94, +=Cohort95, ^=Cohort97"; footnote2 height=2 "Blue line=OLS line; Green lines=95% confidence intervals; Size of the bubbles=Number of students enrolled; Square inside=Minimum value"; symbol1 interpol=RLCLM95 ci=blue co=green width=2 value=diamond height=3 pointlabel=("#city2"); axis1 offset=(5,5) pct label=("&h_label") ; axis2 label=( a=90 r=0) ; proc gplot data=all2; where &flag=1; plot &outcome*&factor / haxis=axis1 vaxis=axis2 regeqn; bubble2 &outcome*&factor=stdsize / noaxis bcolor=red; *format &outcome percent8.0; format total_enroll_alge1 percent8.0; format total_enroll_himath percent8.0; format total_enroll_allsci percent8.0; format N1K_APmathtaker comma10.0; format N1K_APscitaker comma10.0; label &outcome="&v_label"; run; quit; Filename GIFOUT Clear; ods rtf file="&STORE.&taitoru1..rtf" /* style=minimal*/; proc report data=all2 nowd headline colwidth=8 spacing=1; title5 "RAW DATA"; where &flag=1; column city cohort_name color &outcome &factor stdsize; define &outcome / "&v_label"; define &factor /"&h_label"; define stdsize /"Student Population Size" format=comma10.0; run; ods rtf close; Filename GIFOUT "D:\systemic\final report\&name..gif"; *ods trace on; *ods listing close; proc reg data=all2; where &flag=1; model &outcome=&factor; ODS output fitstatistics=F&ID anova=A&ID parameterestimates=PP&ID; run; *ods listing; *ods trace off; data PP1&ID;set PP&ID; keep ID intercept intercept_error intercept_p; jun=_n_; if jun=1; intercept=Estimate; intercept_error=stderr; intercept_p=probt; length ID $ 30; ID="&outcome&factor"; run; data PP2&ID;set PP&ID; keep ID var1 var1_error var1_p; jun=_n_; if jun=2; var1=Estimate; var1_error=stderr; var1_p=probt; ID="&outcome&factor"; run; data Pall&ID;merge PP1&ID PP2&ID;by ID;run; proc print;run; data A1&ID;set A&ID; keep ID Fvalue ProbF; jun=_n_; if jun=1; ID="&outcome&factor"; run; data F&ID;set F&ID; keep ID Rsquare; jun=_n_; if jun=1; Rsquare=Cvalue2; ID="&outcome&factor"; run; data data&ID; merge Pall&ID A1&ID F&ID; by ID; x="&taitoru1"; length col1 $ 25; col1=substr(X,9,10); drop x; %mend for_graph; *%for_graph (flag=,outcome=total_enroll_alge1, factor=W_rubric1, taitoru1=Exibit 39 EA1A, taitoru2=Algebra 1: Annualized Enrollment Percentage Point Increase, taitoru3=Versus Rubric 1 Equal Access Weighted by Time Factor, h_label=Rubric 1, v_label=Enrollment); /*When updating, use an excell sheet "Bivariate Relations.xls"*/ *%for_graph (flag=,outcome= total_enroll_alge1 ,taitoru1= Exhibit X-1 a A1E_R1 ,v_label= Enrollment ,taitoru2= Algebra 1 : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 1: Equal Access ,h_label= Rubric 1 ,factor= W_Rubric1 ,select=alge1 ); *%for_graph (flag=,outcome= total_enroll_alge1 ,taitoru1= Exhibit X-1 b A1E_R1_1 ,v_label= Enrollment ,taitoru2= Algebra 1 : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 1.1 Elimination of Tracking ,h_label= Rubric 1.1 ,factor= W_Rubric1_1 ,select=alge1 ); *%for_graph (flag=,outcome= total_enroll_alge1 ,taitoru1= Exhibit X-1 c A1E_R1_2 ,v_label= Enrollment ,taitoru2= Algebra 1 : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 1.2 More Upper Level Courses ,h_label= Rubric 1.2 ,factor= W_Rubric1_2 ,select=alge1 ); *%for_graph (flag=,outcome= total_enroll_alge1 ,taitoru1= Exhibit X-1 d A1E_R3 ,v_label= Enrollment ,taitoru2= Algebra 1 : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 3 Graduation and Promotion Policy ,h_label= Rubric 3 ,factor= W_Rubric3 ,select=alge1 ); *%for_graph (flag=,outcome= total_enroll_alge1 ,taitoru1= Exhibit X-1 e A1E_R3_1 ,v_label= Enrollment ,taitoru2= Algebra 1 : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 3.1 Graduation Requirements More Rigorous than the State ,h_label= Rubric 3.1 ,factor= W_Rubric3_1 ,select=alge1 ); *%for_graph (flag=,outcome= total_enroll_alge1 ,taitoru1= Exhibit X-1 f A1E_R3_2 ,v_label= Enrollment ,taitoru2= Algebra 1 : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 3.2 Graduation Requirements of at Least 3 Years of Mathematics and Science ,h_label= Rubric 3.2 ,factor= W_Rubric3_2 ,select=alge1 ); *%for_graph (flag=,outcome= total_enroll_alge1 ,taitoru1= Exhibit X-1 g A1E_R1R3 ,v_label= Enrollment ,taitoru2= Algebra 1 : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric1 & 3 Equal Access and Graduation & Promotion Policy ,h_label= Rubric1 & 3 ,factor= W_Rubric1and3 ,select=alge1 ); *%for_graph (flag=,outcome= total_enroll_alge1 ,taitoru1= Exhibit X-1 h A1E_R2 ,v_label= Enrollment ,taitoru2= Algebra 1 : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 2 Student Support Programs ,h_label= Rubric 2 ,factor= W_Rubric2 ,select=alge1 ); *%for_graph (flag=,outcome= total_enroll_alge1 ,taitoru1= Exhibit X-1 i A1E_R2_1 ,v_label= Enrollment ,taitoru2= Algebra 1 : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 2.1 Strategies to Address Needs of Special Populations ,h_label= Rubric 2.1 ,factor= W_Rubric2_1 ,select=alge1 ); *%for_graph (flag=,outcome= total_enroll_alge1 ,taitoru1= Exhibit X-1 j A1E_R2_2 ,v_label= Enrollment ,taitoru2= Algebra 1 : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 2.2 Targeted Programs for Underrepresented Minorities ,h_label= Rubric 2.2 ,factor= W_Rubric2_2 ,select=alge1 ); *%for_graph (flag=,outcome= total_enroll_alge1 ,taitoru1= Exhibit X-1 k A1E_R4 ,v_label= Enrollment ,taitoru2= Algebra 1 : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric4 Attendence and Safety Net Programs ,h_label= Rubric4 ,factor= W_Rubric4 ,select=alge1 ); *%for_graph (flag=,outcome= total_enroll_alge1 ,taitoru1= Exhibit X-1 l A1E_R2R4 ,v_label= Enrollment ,taitoru2= Algebra 1 : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric2 & 4 Student Support Programs and Attendence and Safety Net Programs ,h_label= Rubric2 & 4 ,factor= W_Rubric2and4 ,select=alge1 ); %for_graph (ID=1,flag=nocleveland,outcome= total_enroll_himath ,taitoru1= Exhibit X-1 a ME_R1 ,v_label= Enrollment ,taitoru2= Higher Math : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 1: Equal Access ,h_label= Rubric 1 ,factor= W_Rubric1 ,select=himath ); %for_graph (ID=2,flag=nocleveland,outcome= total_enroll_himath ,taitoru1= Exhibit X-1 b ME_R1_1 ,v_label= Enrollment ,taitoru2= Higher Math : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 1.1 Elimination of Tracking ,h_label= Rubric 1.1 ,factor= W_Rubric1_1 ,select=himath ); %for_graph (ID=3,flag=nocleveland,outcome= total_enroll_himath ,taitoru1= Exhibit X-1 c ME_R1_2 ,v_label= Enrollment ,taitoru2= Higher Math : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 1.2 More Upper Level Courses ,h_label= Rubric 1.2 ,factor= W_Rubric1_2 ,select=himath ); %for_graph (ID=4,flag=nocleveland,outcome= total_enroll_himath ,taitoru1= Exhibit X-1 d ME_R3 ,v_label= Enrollment ,taitoru2= Higher Math : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 3 Graduation and Promotion Policy ,h_label= Rubric 3 ,factor= W_Rubric3 ,select=himath ); %for_graph (ID=5,flag=nocleveland,outcome= total_enroll_himath ,taitoru1= Exhibit X-1 e ME_R3_1 ,v_label= Enrollment ,taitoru2= Higher Math : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 3.1 Graduation Requirements More Rigorous than the State ,h_label= Rubric 3.1 ,factor= W_Rubric3_1 ,select=himath ); %for_graph (ID=6,flag=nocleveland,outcome= total_enroll_himath ,taitoru1= Exhibit X-1 f ME_R3_2 ,v_label= Enrollment ,taitoru2= Higher Math : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 3.2 Graduation Requirements of at Least 3 Years of Mathematics and Science ,h_label= Rubric 3.2 ,factor= W_Rubric3_2 ,select=himath ); %for_graph (ID=7,flag=nocleveland,outcome= total_enroll_himath ,taitoru1= Exhibit X-1 g ME_R1R3 ,v_label= Enrollment ,taitoru2= Higher Math : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric1 & 3 Equal Access and Graduation & Promotion Policy ,h_label= Rubric1 & 3 ,factor= W_Rubric1and3 ,select=himath ); %for_graph (ID=8,flag=nocleveland,outcome= total_enroll_himath ,taitoru1= Exhibit X-1 h ME_R2 ,v_label= Enrollment ,taitoru2= Higher Math : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 2 Student Support Programs ,h_label= Rubric 2 ,factor= W_Rubric2 ,select=himath ); %for_graph (ID=9,flag=nocleveland,outcome= total_enroll_himath ,taitoru1= Exhibit X-1 i ME_R2_1 ,v_label= Enrollment ,taitoru2= Higher Math : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 2.1 Strategies to Address Needs of Special Populations ,h_label= Rubric 2.1 ,factor= W_Rubric2_1 ,select=himath ); %for_graph (ID=10,flag=nocleveland,outcome= total_enroll_himath ,taitoru1= Exhibit X-1 j ME_R2_2 ,v_label= Enrollment ,taitoru2= Higher Math : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 2.2 Targeted Programs for Underrepresented Minorities ,h_label= Rubric 2.2 ,factor= W_Rubric2_2 ,select=himath ); %for_graph (ID=11,flag=nocleveland,outcome= total_enroll_himath ,taitoru1= Exhibit X-1 k ME_R4 ,v_label= Enrollment ,taitoru2= Higher Math : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric4 Attendence and Safety Net Programs ,h_label= Rubric4 ,factor= W_Rubric4 ,select=himath ); %for_graph (ID=12,flag=nocleveland,outcome= total_enroll_himath ,taitoru1= Exhibit X-1 l ME_R2R4 ,v_label= Enrollment ,taitoru2= Higher Math : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric2 & 4 Student Support Programs and Attendence and Safety Net Programs ,h_label= Rubric2 & 4 ,factor= W_Rubric2and4 ,select=himath ); %for_graph (ID=13,flag=flag,outcome= total_enroll_allsci ,taitoru1= Exhibit X-2 a SE_R1 ,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 1: Equal Access ,h_label= Rubric 1 ,factor= W_Rubric1 ,select=allsci ); %for_graph (ID=14,flag=flag,outcome= total_enroll_allsci ,taitoru1= Exhibit X-2 b SE_R1_1 ,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 1.1 Elimination of Tracking ,h_label= Rubric 1.1 ,factor= W_Rubric1_1 ,select=allsci ); %for_graph (ID=15,flag=flag,outcome= total_enroll_allsci ,taitoru1= Exhibit X-2 c SE_R1_2 ,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 1.2 More Upper Level Courses ,h_label= Rubric 1.2 ,factor= W_Rubric1_2 ,select=allsci ); %for_graph (ID=16,flag=flag,outcome= total_enroll_allsci ,taitoru1= Exhibit X-2 d SE_R3 ,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 3 Graduation and Promotion Policy ,h_label= Rubric 3 ,factor= W_Rubric3 ,select=allsci ); %for_graph (ID=17,flag=flag,outcome= total_enroll_allsci ,taitoru1= Exhibit X-2 e SE_R3_1 ,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 3.1 Graduation Requirements More Rigorous than the State ,h_label= Rubric 3.1 ,factor= W_Rubric3_1 ,select=allsci ); %for_graph (ID=18,flag=flag,outcome= total_enroll_allsci ,taitoru1= Exhibit X-2 f SE_R3_2 ,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 3.2 Graduation Requirements of at Least 3 Years of Mathematics and Science ,h_label= Rubric 3.2 ,factor= W_Rubric3_2 ,select=allsci ); %for_graph (ID=19,flag=flag,outcome= total_enroll_allsci ,taitoru1= Exhibit X-2 g SE_R1R3 ,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric1 & 3 Equal Access and Graduation & Promotion Policy ,h_label= Rubric1 & 3 ,factor= W_Rubric1and3 ,select=allsci ); %for_graph (ID=20,flag=flag,outcome= total_enroll_allsci ,taitoru1= Exhibit X-2 h SE_R2 ,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 2 Student Support Programs ,h_label= Rubric 2 ,factor= W_Rubric2 ,select=allsci ); %for_graph (ID=21,flag=flag,outcome= total_enroll_allsci ,taitoru1= Exhibit X-2 i SE_R2_1 ,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 2.1 Strategies to Address Needs of Special Populations ,h_label= Rubric 2.1 ,factor= W_Rubric2_1 ,select=allsci ); %for_graph (ID=22,flag=flag,outcome= total_enroll_allsci ,taitoru1= Exhibit X-2 j SE_R2_2 ,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric 2.2 Targeted Programs for Underrepresented Minorities ,h_label= Rubric 2.2 ,factor= W_Rubric2_2 ,select=allsci ); %for_graph (ID=23,flag=flag,outcome= total_enroll_allsci ,taitoru1= Exhibit X-2 k SE_R4 ,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric4 Attendence and Safety Net Programs ,h_label= Rubric4 ,factor= W_Rubric4 ,select=allsci ); %for_graph (ID=24,flag=flag,outcome= total_enroll_allsci ,taitoru1= Exhibit X-2 l SE_R2R4 ,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric2 & 4 Student Support Programs and Attendence and Safety Net Programs ,h_label= Rubric2 & 4 ,factor= W_Rubric2and4 ,select=allsci ); %for_graph (ID=25,flag=flag,outcome= total_n1k_APmathtaker ,taitoru1= Exhibit XI-1 a APMT_R1 ,v_label= AP Tests Taken ,taitoru2= Mathematics AP Tests Taken : Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 1: Equal Access ,h_label= Rubric 1 ,factor= W_Rubric1 ,select=all ); %for_graph (ID=26,flag=flag,outcome= total_n1k_APmathtaker ,taitoru1= Exhibit XI-1 b APMT_R1_1 ,v_label= AP Tests Taken ,taitoru2= Mathematics AP Tests Taken: Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 1.1 Elimination of Tracking ,h_label= Rubric 1.1 ,factor= W_Rubric1_1 ,select=all ); %for_graph (ID=27,flag=flag,outcome= total_n1k_APmathtaker ,taitoru1= Exhibit XI-1 c APMT_R1_2 ,v_label= AP Tests Taken ,taitoru2= Mathematics AP Tests Taken : Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 1.2 More Upper Level Courses ,h_label= Rubric 1.2 ,factor= W_Rubric1_2 ,select=all ); %for_graph (ID=28,flag=flag,outcome= total_n1k_APmathtaker ,taitoru1= Exhibit XI-1 d APMT_R3 ,v_label= AP Tests Taken ,taitoru2= Mathematics AP Tests Taken : Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 3 Graduation and Promotion Policy ,h_label= Rubric 3 ,factor= W_Rubric3 ,select=all ); %for_graph (ID=29,flag=flag,outcome= total_n1k_APmathtaker ,taitoru1= Exhibit XI-1 e APMT_R3_1 ,v_label= AP Tests Taken ,taitoru2= Mathematics AP Tests Taken: Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 3.1 Graduation Requirements More Rigorous than the State ,h_label= Rubric 3.1 ,factor= W_Rubric3_1 ,select=all ); %for_graph (ID=30,flag=flag,outcome= total_n1k_APmathtaker ,taitoru1= Exhibit XI-1 f APMT_R3_2 ,v_label= AP Tests Taken ,taitoru2= Mathematics AP Tests Taken : Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 3.2 Graduation Requirements of at Least 3 Years of Mathematics and Science ,h_label= Rubric 3.2 ,factor= W_Rubric3_2 ,select=all ); %for_graph (ID=31,flag=flag,outcome= total_n1k_APmathtaker ,taitoru1= Exhibit XI-1 g APMT_R1R3 ,v_label= AP Tests Taken ,taitoru2= Mathematics AP Tmaticsests Taken: Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric1 & 3 Equal Access and Graduation & Promotion Policy ,h_label= Rubric1 & 3 ,factor= W_Rubric1and3 ,select=all ); %for_graph (ID=32,flag=flag,outcome= total_n1k_APmathtaker ,taitoru1= Exhibit XI-1 h APMT_R2 ,v_label= AP Tests Taken ,taitoru2= Mathematics AP Tests Taken : Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 2 Student Support Programs ,h_label= Rubric 2 ,factor= W_Rubric2 ,select=all ); %for_graph (ID=33,flag=flag,outcome= total_n1k_APmathtaker ,taitoru1= Exhibit XI-1 i APMT_R2_1 ,v_label= AP Tests Taken ,taitoru2= Mathematics AP Tests Taken: Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 2.1 Strategies to Address Needs of Special Populations ,h_label= Rubric 2.1 ,factor= W_Rubric2_1 ,select=all ); %for_graph (ID=34,flag=flag,outcome= total_n1k_APmathtaker ,taitoru1= Exhibit XI-1 j APMT_R2_2 ,v_label= AP Tests Taken ,taitoru2= Mathematics AP Tests Taken: Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 2.2 Targeted Programs for Underrepresented Minorities ,h_label= Rubric 2.2 ,factor= W_Rubric2_2 ,select=all ); %for_graph (ID=35,flag=flag,outcome= total_n1k_APmathtaker ,taitoru1= Exhibit XI-1 k APMT_R4 ,v_label= AP Tests Taken ,taitoru2= Mathematics AP Tests Taken: Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric4 Attendence and Safety Net Programs ,h_label= Rubric4 ,factor= W_Rubric4 ,select=all ); %for_graph (ID=36,flag=flag,outcome= total_n1k_APmathtaker ,taitoru1= Exhibit XI-1 l APM_R2R4 ,v_label= AP Tests Taken ,taitoru2= Mathematics AP Tests Taken: Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric2 & 4 Student Support Programs and Attendence and Safety Net Programs ,h_label= Rubric2 & 4 ,factor= W_Rubric2and4 ,select=all ); %for_graph (ID=37,flag=flag,outcome= total_n1k_APscitaker ,taitoru1= Exhibit XI-2 a APST_R1 ,v_label= AP Tests Taken ,taitoru2= Science AP Tests Taken : Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 1: Equal Access ,h_label= Rubric 1 ,factor= W_Rubric1 ,select=all ); %for_graph (ID=38,flag=flag,outcome= total_n1k_APscitaker ,taitoru1= Exhibit XI-2 b APST_R1_1 ,v_label= AP Tests Taken ,taitoru2= Science AP Tests Taken: Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 1.1 Elimination of Tracking ,h_label= Rubric 1.1 ,factor= W_Rubric1_1 ,select=all ); %for_graph (ID=39,flag=flag,outcome= total_n1k_APscitaker ,taitoru1= Exhibit XI-2 c APST_R1_2 ,v_label= AP Tests Taken ,taitoru2= Science AP Tests Taken: Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 1.2 More Upper Level Courses ,h_label= Rubric 1.2 ,factor= W_Rubric1_2 ,select=all ); %for_graph (ID=40,flag=flag,outcome= total_n1k_APscitaker ,taitoru1= Exhibit XI-2 d APST_R3 ,v_label= AP Tests Taken ,taitoru2= Science AP Tests Taken: Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 3 Graduation and Promotion Policy ,h_label= Rubric 3 ,factor= W_Rubric3 ,select=all ); %for_graph (ID=41,flag=flag,outcome= total_n1k_APscitaker ,taitoru1= Exhibit XI-2 e APST_R3_1 ,v_label= AP Tests Taken ,taitoru2= ScienceAP Tests Taken : Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 3.1 Graduation Requirements More Rigorous than the State ,h_label= Rubric 3.1 ,factor= W_Rubric3_1 ,select=all ); %for_graph (ID=42,flag=flag,outcome= total_n1k_APscitaker ,taitoru1= Exhibit XI-2 f APST_R3_2 ,v_label= AP Tests Taken ,taitoru2= ScienceAP Tests Taken : Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 3.2 Graduation Requirements of at Least 3 Years of Mathematics and Science ,h_label= Rubric 3.2 ,factor= W_Rubric3_2 ,select=all ); %for_graph (ID=43,flag=flag,outcome= total_n1k_APscitaker ,taitoru1= Exhibit XI-2 g APST_R1R3 ,v_label= AP Tests Taken ,taitoru2= Science AP Tests Taken : Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric1 & 3 Equal Access and Graduation & Promotion Policy ,h_label= Rubric1 & 3 ,factor= W_Rubric1and3 ,select=all ); %for_graph (ID=44,flag=flag,outcome= total_n1k_APscitaker ,taitoru1= Exhibit XI-2 h APST_R2 ,v_label= AP Tests Taken ,taitoru2= Science AP Tests Taken : Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 2 Student Support Programs ,h_label= Rubric 2 ,factor= W_Rubric2 ,select=all ); %for_graph (ID=45,flag=flag,outcome= total_n1k_APscitaker ,taitoru1= Exhibit XI-2 i APST_R2_1 ,v_label= AP Tests Taken ,taitoru2= Science AP Tests Taken : Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 2.1 Strategies to Address Needs of Special Populations ,h_label= Rubric 2.1 ,factor= W_Rubric2_1 ,select=all ); %for_graph (ID=46,flag=flag,outcome= total_n1k_APscitaker ,taitoru1= Exhibit XI-2 j APST_R2_2 ,v_label= AP Tests Taken ,taitoru2= Science AP Tests Taken : Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric 2.2 Targeted Programs for Underrepresented Minorities ,h_label= Rubric 2.2 ,factor= W_Rubric2_2 ,select=all ); %for_graph (ID=47,flag=flag,outcome= total_n1k_APscitaker ,taitoru1= Exhibit XI-2 k APST_R4 ,v_label= AP Tests Taken ,taitoru2= Science AP Tests Taken : Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric4 Attendence and Safety Net Programs ,h_label= Rubric4 ,factor= W_Rubric4 ,select=all ); %for_graph (ID=48,flag=flag,outcome= total_n1k_APscitaker ,taitoru1= Exhibit XI-2 l APS_R2R4 ,v_label= AP Tests Taken ,taitoru2= Science : Annualized Test-Taking Percentage Point Increase ,taitoru3= Rubric2 & 4 Student Support Programs and Attendence and Safety Net Programs ,h_label= Rubric2 & 4 ,factor= W_Rubric2and4 ,select=all ); /*new addition per Ana's request*/ %for_graph (ID=49,flag=nocleveland,outcome= total_enroll_himath ,taitoru1= Exhibit new-1 ,v_label= Enrollment ,taitoru2= Higher Math : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric7 Teacher Qualifications ,h_label= Rubri7 ,factor= W_Rubric7 ,select=himath ); %for_graph (ID=50,flag=nocleveland,outcome= total_enroll_allsci ,taitoru1= Exhibit new-2 ,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric7 Teacher Qualifications,h_label= Rubric7 ,factor= W_Rubric7 ,select=allsci ); %for_graph (ID=51,flag=nocleveland,outcome= total_enroll_himath,taitoru1= Exhibit new-3 ,v_label= Enrollment ,taitoru2= Higher Math : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric8 & 9 PD: Contents/Knowledge Participation/Evalution ,h_label= Rubric8 & 9 ,factor= W_Rubric8and9 ,select=himath ); %for_graph (ID=52,flag=flag,outcome= total_enroll_allsci ,taitoru1= Exhibit new-4,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric8 & 9 PD: Contents/Knowledge Participation/Evalution ,h_label= Rubric8 & 9 ,factor= W_Rubric8and9 ,select=allsci ); /*another request*/ %for_graph (ID=51b,flag=nocleveland,outcome= total_enroll_allsci ,taitoru1= Exhibit new-3b ,v_label= Enrollment ,taitoru2= Science : Annualized Enrollment Percentage Point Increase ,taitoru3= Rubric8 & 9 PD: Contents/Knowledge Participation/Evalution ,h_label= Rubric8 & 9 ,factor= W_Rubric8and9 ,select=allsci ); data allregression; set data1 data2 data3 data4 data5 data6 data7 data8 data9 data10 data11 data12 data13 data14 data15 data16 data17 data18 data19 data20 data21 data22 data23 data24 data25 data26 data27 data28 data29 data30 data31 data32 data33 data34 data35 data36 data37 data38 data39 data40 data41 data42 data43 data44 data45 data46 data47 data48 data49 data50 data51 data52 data51b ; proc report data=allregression nowd headline colwidth=5 spacing=1 ; title1 "Regression Results"; column col1 intercept var1 var1_error var1_p Rsquare Fvalue ProbF; define col1 /"table" width=10; define intercept/"intercept" format=comma6.3; define var1 /"var" format=comma6.3; define var1_error/"error" format=comma6.3; define var1_p/"P" format=comma6.3; define Rsquare/"R2" ; define Fvalue/"F" format=comma6.3; define ProbF/"ProbF" format=comma6.3; run; quit; *break after effect / skip ; /*Accuracy check of annualization*/ /*END OF THE PROGRAM*/ /* data enro_C;length city $ 13;set here2.enrollment_City; keep city A_GAP_compl_allsci A_GAP_enroll_allsci A_GAP_passing_allsci A_Gap_compl_alge1 A_Gap_compl_himath A_Gap_enroll_alge1 A_Gap_enroll_himath A_Gap_passing_alge1 A_Gap_passing_himath A_Total_compl_alge1 A_Total_compl_allsci A_Total_compl_himath A_Total_enroll_alge1 A_Total_enroll_allsci A_Total_enroll_himath A_Total_passing_alge1 A_Total_passing_allsci A_Total_passing_himath; A_GAP_compl_allsci =GAP_compl_allsci; A_GAP_enroll_allsci =GAP_enroll_allsci; A_GAP_passing_allsci = GAP_passing_allsci; A_Gap_compl_alge1 =Gap_compl_alge1; A_Gap_compl_himath = Gap_compl_himath; A_Gap_enroll_alge1 =Gap_enroll_alge1; A_Gap_enroll_himath = Gap_enroll_himath; A_Gap_passing_alge1 = Gap_passing_alge1; A_Gap_passing_himath = Gap_passing_himath; A_Total_compl_alge1 = Total_compl_alge1; A_Total_compl_allsci = Total_compl_allsci; A_Total_compl_himath = Total_compl_himath; A_Total_enroll_alge1 = Total_enroll_alge1; A_Total_enroll_allsci =Total_enroll_allsci; A_Total_enroll_himath = Total_enroll_himath; A_Total_passing_alge1 = Total_passing_alge1; A_Total_passing_allsci = Total_passing_allsci; A_Total_passing_himath = Total_passing_himath; ***; proc sort;by city;run;*/ data enro_CY;length city $ 13;set here2.enrollment_CityYEAR; if year ne 2000;/*don't use year 2000*/ if city ne "Houston"; if city ne "Hypothetical"; if city ne "New Orleans"; if city="Baltimore" and year=1993 then do; total_himathe=6106.1; total_allscie=12497.1; imp_total_himathe="*"; imp_total_allscie="*"; end; if city="Detroit" and year=1993 then do; /* total_grade8=abs(mean(10978, 10679); imp_total_grade8="*"; */ ur_grade8=abs(mean( 19276, 9975 ))+.1000; ur_grade9to12=abs(mean ( 38525, 37506))+.1000; imp_ur_grade8="*"; imp_ur_grade9to12="*"; end; if city="Detroit" and year=1996 then do; ur_grade8=abs((9975+9822)/2)+.1000; ur_grade9to12=abs((37506+36605)/2)+.1000; imp_ur_grade8="*"; imp_ur_grade9to12="*"; end; /*fix irregularity*/ if city ="Detroit" and year=1997 then do; ur_alge1e=abs(1145/10); end; if city="Detroit" and (year=1998 or year=1999) then do; ur_grade8=abs((9899+9822)/2)+.1000; ur_grade9to12=abs((37056+36605)/2)+.1000; ur_himathe=abs((15362+25181)/2)+.1000; ur_allscie=abs((16940+16489)/2)+.1000; ur_alge1e=abs((114+150)/2)+.1000; imp_ur_grade8="*"; imp_ur_grade9to12="*"; imp_ur_himathe="*"; imp_ur_allscie="*"; imp_ur_alge1e="*"; end; exclude_totale_data=0; if /*city ="Dallas" or*/ city ="Detroit" or city ="El Paso" or city ="Phenix" then do; exclude_totale_data=1; total_himathe=.; total_allscie=.; total_alge1e=.; end; exclude_ure_data=0; if city= "Baltimore" or city="El Paso" then do; exclude_ure_data=1; ur_himathe=.; ur_allscie=.; ur_alge1e=.; end; exclude_totalc_data=0; if city="Baltimore" or city="El Paso" or city="Detroit" or city="Milwaukee" then do; exclude_totalc_data=1; total_himathc=.; total_allscic=.; total_alge1c=.; end; exclude_urc_data=0; if city="Baltimore" or city="El Paso" or city="Detroit" or city="Phoenix" or city="Milwaukee" then do; exclude_urc_data=1; ur_himathc=.; ur_allscic=.; ur_alge1c=.; end; exclude_alge1E=0; if city="Cleveland" then do; exclude_alge1E=1; total_alge1e=.; end; /* exclude_totalc_alge1_data=0; if city="Cleveland" then do; exclude_totalc_alge1_data=1; end;*/ *exclude_urc_data=0; /*for cohort 93*/ if city="Cleveland" and year=1994 then do; *total_himathe=abs(mean( 4547 ,7497))+.1000; total_himathe=6022.1; *total_allscie=abs(mean(5129, 5266))+.1000; total_allscie=5198.1; imp_total_himathe="*"; imp_total_allscie="*"; ur_himathe=abs((3643+6151/2))+.1000; imp_ur_himathe="*"; ur_allscie=abs((4118+4345/2))+.1000; imp_ur_allscie="*"; total_allscic=abs((3519+3676)/2)+.1000; total_himathc=abs((2849+4327)/2)+.1000; imp_total_himathc="*"; imp_total_allscic="*"; ur_allscic=abs(mean(2792 , 3007))+.1000; ur_himathc=abs(mean(2221 , 3479 ))+.1000; imp_ur_himathc="*"; imp_ur_allscic="*"; end; if city="Cleveland" and year=1999 then do; total_himathe=10668.1; total_allscie=5474.1; total_grade9to12=16032.1; ur_himathe=abs(mean (4568, 8839))+.1000; ur_allscie=abs(mean(4853 , 4448))+.1000; ur_grade9to12=abs(mean(14053, 13140))+.1000; imp_total_himathe="*"; imp_total_allscie="*"; imp_total_grade9to12="*"; imp_ur_himathe="*"; imp_ur_allscie="*"; imp_ur_grade9to12="*"; total_allscic=abs(mean(4200 , 4018 ))+.1000; total_himathc=abs(mean(3724 , 6759 ))+.1000; imp_total_himathc="*"; imp_total_allscic="*"; ur_allscic=abs(mean(3224 ,3430))+.1000; ur_himathc=abs(mean(3007 ,5455 ))+.1000; imp_ur_himathc="*"; imp_ur_allscic="*"; end; /*all cities for cohort 93 are used*/ /*cohort 95*/ if city="Milwaukee" and (year=1995 or year=1996) then do; total_himathe=abs(mean(2582 , 9204))+.1000; total_allscie=abs(mean( 3265, 9423))+.1000; total_alge1e=abs(mean( 1070, 1372 ))+.1000; imp_total_himathe="*"; imp_total_allscie="*"; imp_total_alge1e="*"; ur_himathe=abs(mean(1761 ,6219))+.1000; ur_allscie=abs(mean( 2262, 6493))+.1000; ur_alge1e=abs(mean( 693, 966 ))+.1000; imp_ur_himathe="*"; imp_ur_allscie="*"; imp_ur_alge1e="*"; end; /*to impute an irregular number*/ if city ="San Diego" and year=1997 then do; total_alge1e=abs(mean(9328, 10269))+.1000; imp_total_alge1e="*"; ur_alge1e=abs(mean( 4442, 5038 ))+.1000; imp_ur_alge1e="*"; total_allscic=abs(mean( 12053 , 12582 ))+.1000; total_himathc=abs(mean(10775 , 11587 ))+.1000; total_alge1c=abs(mean(7940 , 8625 ))+.1000; imp_total_himathc="*"; imp_total_allscic="*"; imp_total_alge1c="*"; ur_allscic=abs(mean(4714 , 4819 ))+.1000; ur_himathc=abs(mean(3553 , 3958 ))+.1000; ur_alge1c=abs(mean(3473 , 3858 ))+.1000; imp_ur_himathc="*"; imp_ur_allscic="*"; imp_ur_alge1c="*"; end; if city ="San Diego" and year=1999 then do; total_alge1e=abs(mean( 9798.5, 10269))+.1000; imp_total_alge1e="*"; ur_alge1e=abs(mean( 4740, 5038 ))+.1000; imp_ur_alge1e="*"; total_allscic=abs(mean( 12582 , 12317 ))+.1000; total_himathc=abs(mean(11587 , 11181 ))+.1000; total_alge1c=abs(mean(8625 , 8282 ))+.1000; imp_total_himathc="*"; imp_total_allscic="*"; imp_total_alge1c="*"; ur_allscic=abs(mean(4768,4819 ))+.1000; ur_himathc=abs(mean(3755.5 , 3958))+.1000; ur_alge1c=abs(mean(3663 , 3853))+.1000; imp_ur_himathc="*"; imp_ur_allscic="*"; imp_ur_alge1c="*"; end; *******************************************************; *******************************************************; /*Last minute removal of cities*/ /*Dallas has an error in Algebra data, so remove values here2*/ /*February 27th, 2002*/ if city="Dallas" then do; total_alge1e=.; ur_alge1e=.; end; /*We received some updated data from Baltimore. Apparently Math and Science Course Enrollment prior to 1996-1997 is not correct and are not available. */ /*march 3rd*/ if city="Baltimore" then do; total_himathe=.; total_allscie=.; total_himathc=.; total_allscic=.; ur_himathe=.; ur_allscie=.; ur_himathc=.; ur_allscic=.; end; *******************************************************; *******************************************************; /*cohort lables*/ if city= 'Hypothetical' or city='Chicago' or city='Baltimore' or city='Dallas' or city='Detroit' or city='El Paso' or city='Miami' or city='New York' or city='Phoenix' then do; /*give various cohort names for later convinience*/ cohort=1;cohort2=93;cohort_name="Cohort 93";end; if city='Cleveland' or city='Columbus' or city='Fresno' or city='Los Angeles' or city='Memphis' or city='New Orleans' or city='Philadelphia' then do;cohort=2;cohort2=94;cohort_name="Cohort 94";end; if city='Milwaukee' or city= 'St. Louis' or city= 'San Antonio' or city= 'San Diego' then do;cohort=3;cohort2=95;cohort_name="Cohort 95";end; if city='Atlanta' or city='Jacksonville' then do; cohort=4; cohort2=97;cohort_name="Cohort 97";end; if city='Houston' then do;cohort=5;cohort2=99;cohort_name="Cohort 99";end; /*Creating dummy indicators for cities to be used*/ /*here2 DECIDE WHICH CITIES TO INCLUDE*/ use_alge1=1; use_himath=1; use_allsci=1; /*exclusion flags*/ Xtotal_enroll_himath=1; Xtotal_enroll_allsci=1; if city="Chicago" or city="Dallas" or city="Miami" or city="New York" or city="Cleveland" or city="Columbus" or city="Fresno" or city="Los Angeles" or city="Memphis" or city="Philadelphia" or city="Milwaukee" or city="San Antonio" or city="San Diego" or city="St. Louis" or city="Atlanta" or city="Jacksonville" then do; Xtotal_enroll_himath=0; Xtotal_enroll_allsci=0; end; Xur_enroll_himath=1; Xur_enroll_allsci=1; if city="Chicago" or city="Dallas" or city="Detroit" or city="Miami" or city="New York" or city="Cleveland" or city="Columbus" or city="Fresno" or city="Los Angeles" or city="Memphis" or city="Philadelphia" or city="Milwaukee" or city="San Antonio" or city="San Diego" or city="St. Louis" or city="Atlanta" or city="Jacksonville" then do; Xur_enroll_himath=0; Xur_enroll_allsci=0; end; Xtotal_compl_himath=1; Xtotal_compl_allsci=1; if city="Chicago" or city="Dallas" or city="Miami" or city="New York" or city="Cleveland" or city="Columbus" or city="Fresno" or city="Los Angeles" or city="Memphis" or city="Philadelphia" or city="San Antonio" or city="San Diego" or city="St. Louis" or city="Atlanta" or city="Jacksonville" then do; Xtotal_compl_himath=0; Xtotal_compl_allsci=0; end; Xur_compl_himath=1; Xur_compl_allsci=1; if city="Chicago" or city="Dallas" or city="Miami" or city="New York" or city="Cleveland" or city="Columbus" or city="Fresno" or city="Los Angeles" or city="Memphis" or city="Philadelphia" or city="San Antonio" or city="San Diego" or city="St. Louis" or city="Atlanta" or city="Jacksonville" then do; Xur_compl_himath=0; Xur_compl_allsci=0; end; Xtotal_enroll_alge1=1; if city="Chicago" or city="Miami" or city="New York" or city="Columbus" or city="Fresno" or city="Los Angeles" or city="Memphis" or city="Philadelphia" or city="Milwaukee" or city="San Antonio" or city="San Diego" or city="Atlanta" or city="Jacksonville" then do; Xtotal_enroll_alge1=0; end; Xur_enroll_alge1=1; if city="Detroit" or city="Miami" or city="Columbus" or city="Fresno" or city="Los Angeles" or city="Memphis" or city="Philadelphia" or city="Milwaukee" or city="San Antonio" or city="San Diego" or city="Atlanta" or city="Jacksonville" then do; Xur_enroll_alge1=0; end; proc sort ;by cohort_name city;run; %macro saigo (taitoru1=,taitoru2=,total_alge1e=,total_grade8=,total_enroll_alge1=,cate=); data enro_cyB; set enro_cy; if X&total_enroll_alge1=0; run; proc transpose data=enro_cyB out=enro_cyT; var &total_alge1e &total_grade8 &total_enroll_alge1 ; by cohort_name city; id year; run; proc sort data=enro_cyT;by city;run; /* data enro;merge enro_c enro_cyT; by city; run; */ proc sort data=enro_cyT out=enro; by cohort_name city;run; data enro2; set enro; if _name_="Total_alge1E" then _name_="#Enrolled"; if _name_="Total_himathE" then _name_="#Enrolled"; if _name_="Total_allsciE" then _name_="#Enrolled"; if _name_="Total_alge1C" then _name_="#Completed"; if _name_="Total_himathC" then _name_="#Completed"; if _name_="Total_allsciC" then _name_="#Completed"; if _name_="Total_enroll_alge1" then _name_='%Enrolled'; if _name_="Total_enroll_himath" then _name_='%Enrolled'; if _name_="Total_enroll_allsci" then _name_='%Enrolled'; if _name_="Total_compl_alge1" then _name_='%Completed'; if _name_="Total_compl_himath" then _name_='%Completed'; if _name_="Total_compl_allsci" then _name_='%Completed'; if _name_="Total_grade8" then _name_="#G8 Students"; if _name_="Total_grade9to12" then _name_="#G9-12 Students"; if _name_="UR_alge1E" then _name_="#Enrolled"; if _name_="UR_himathE" then _name_="#Enrolled"; if _name_="UR_allsciE" then _name_="#Enrolled"; if _name_="UR_alge1C" then _name_="#Completed"; if _name_="UR_himathC" then _name_="#Completed"; if _name_="UR_allsciC" then _name_="#Completed"; if _name_="UR_enroll_alge1" then _name_='%Enrolled'; if _name_="UR_enroll_himath" then _name_='%Enrolled'; if _name_="UR_enroll_allsci" then _name_='%Enrolled'; if _name_="UR_compl_alge1" then _name_='%Completed'; if _name_="UR_compl_himath" then _name_='%Completed'; if _name_="UR_compl_allsci" then _name_='%Completed'; if _name_="UR_grade8" then _name_="#G8 Students"; if _name_="UR_grade9to12" then _name_="#G9-12 Students"; run; footnote1; proc sort data=enro2 out=enro2S; by cohort_name _name_; run; proc means data=enro2S noprint sum; where _name_ ne '%Completed' and _name_ ne '%Enrolled' and cohort_name ne " "; by cohort_name _name_; var _1993 _1994 _1995 _1996 _1997 _1998 _1999; output out=enroSUM sum=; run; data ENROLLED;set enroSUM; keep cohort_name _name_ _1993E _1994E _1995E _1996E _1997E _1998E _1999E; if _name_="#Enrolled" or _name_="#Completed"; _1993E= _1993 ; _1994E= _1994 ; _1995E= _1995 ; _1996E= _1996 ; _1997E= _1997 ; _1998E= _1998 ; _1999E=_1999; run; data Gstd;set enroSUM; keep cohort_name _name_ _1993G _1994G _1995G _1996G _1997G _1998G _1999G; if _name_="#G9-12 Students" or _name_="#G8 Students"; _1993G= _1993 ; _1994G= _1994 ; _1995G= _1995 ; _1996G= _1996 ; _1997G= _1997 ; _1998G= _1998 ; _1999G=_1999; run; data both;merge enrolled Gstd; by cohort_name ; keep cohort_name _name_ city _1993 _1994 _1995 _1996 _1997 _1998 _1999; array asdf _1993E _1994E _1995E _1996E _1997E _1998E _1999E _1993G _1994G _1995G _1996G _1997G _1998G _1999G; do over asdf; asdf=asdf+0; end; _1993=_1993E/_1993G; _1994=_1994E/_1994G; _1995=_1995E/_1995G; _1996=_1996E/_1996G; _1997=_1997E/_1997G; _1998=_1998E/_1998G; _1999=_1999E/_1999G; city="Total"; A="%"; B="&cate"; _name_=compress(A||B); run; data enrosum2;set enrosum; city="Total"; run; /* data all;set enro2 enrosum2 both ;by cohort_name; keep cohort_name city _name_ _1993 _1994 _1995 _1996 _1997 _1998 _1999 JUN; if cohort_name ne " "; run;*/ data total1993;set enrosum2;if Cohort_name="Cohort 93";run; data total1994;set enrosum2;if Cohort_name="Cohort 94";run; data total1995;set enrosum2;if Cohort_name="Cohort 95";run; data total1997;set enrosum2;if Cohort_name="Cohort 97";run; data totalB1993;set both;if Cohort_name="Cohort 93";run; data totalB1994;set both;if Cohort_name="Cohort 94";run; data totalB1995;set both;if Cohort_name="Cohort 95";run; data totalB1997;set both;if Cohort_name="Cohort 97";run; data main1993;set enro2;if Cohort_name="Cohort 93";run; data main1994;set enro2;if Cohort_name="Cohort 94";run; data main1995;set enro2;if Cohort_name="Cohort 95";run; data main1997;set enro2;if Cohort_name="Cohort 97";run; data allthese; set main1993 total1993 totalB1993 main1994 total1994 totalB1994 main1995 total1995 totalB1995 main1997 total1997 totalB1997;by cohort_name city; if _name_ ne "#Enrolled" and _name_ ne "#Completed" then city=" "; drop _TYPE_ _FREQ_ ; run; proc report data=allthese nowd headline colwidth=5 spacing=1; title1 "&taitoru2"; title2 "&taitoru1"; column cohort_name city _name_ _1993 _1994 _1995 _1996 _1997 _1998 _1999 /* a_&total_enroll_alge1 annual*/; *define city /order order=data " "; define cohort_name /order order=data " "; define _name_ /" "; define _1993 / "1993-1994" format=comma6.3; define _1994 / "1994-1995" format=comma6.3; define _1995 / "1995-1996" format=comma6.3; define _1996 / "1996-1997" format=comma6.3; define _1997 / "1997-1998" format=comma6.3; define _1998 / "1998-1999" format=comma6.3; define _1999 / "1999-2000" format=comma6.3; define a_&total_enroll_alge1/"Annualized" format=percent6.1; break after cohort_name / dol skip ; run; PROC EXPORT DATA= allthese OUTFILE= "&WD2.\&taitoru2..xls" DBMS=EXCEL2000 REPLACE;RUN; %mend saigo; %saigo (taitoru2=Exhibit A-1 Math ,taitoru1=Higher-level Mathematics course Enrollment in 9-12th Grades: All Students, total_alge1e=total_himathe,total_grade8=total_grade9to12,total_enroll_alge1=total_enroll_himath,cate=Enrolled); %saigo (taitoru2=Exhibit A-1 Science ,taitoru1=Science course Enrollment in 9-12th Grades: All Students, total_alge1e=total_allscie,total_grade8=total_grade9to12,total_enroll_alge1=total_enroll_allsci,cate=Enrolled); %saigo (taitoru2=Exhibit A-2 Math ,taitoru1=Higher-level Mathematics course Enrollment in 9-12th Grades: Underrepresented Minority Students, total_alge1e=ur_himathe,total_grade8=ur_grade9to12,total_enroll_alge1=ur_enroll_himath,cate=Enrolled); %saigo (taitoru2=Exhibit A-2 Science ,taitoru1=Science course Enrollment in 9-12th Grades: Underrepresented Minority Students, total_alge1e=ur_allscie,total_grade8=ur_grade9to12,total_enroll_alge1=ur_enroll_allsci,cate=Enrolled); %saigo (taitoru2=Exhibit A-3 Math ,taitoru1=Higher-level Mathematics course Completion in 9-12th Grades: All Students, total_alge1e=total_himathc,total_grade8=total_grade9to12,total_enroll_alge1=total_compl_himath,cate=Completed); %saigo (taitoru2=Exhibit A-3 Science ,taitoru1=Science course Completion in 9-12th Grades: All Students, total_alge1e=total_allscic,total_grade8=total_grade9to12,total_enroll_alge1=total_compl_allsci,cate=Completed); %saigo (taitoru2=Exhibit A-4 Math,taitoru1=Higher-level Mathematics course Completion in 9-12th Grades: Underrepresented Students, total_alge1e=ur_himathc,total_grade8=ur_grade9to12,total_enroll_alge1=ur_compl_himath,cate=Completed); %saigo (taitoru2=Exhibit A-4 Science ,taitoru1=Science course Completion in 9-12th Grades: Underrepresented Students, total_alge1e=ur_allscic,total_grade8=ur_grade9to12,total_enroll_alge1=ur_compl_allsci,cate=Completed); %saigo (taitoru2=Exhibit A-5 Algebra I ,taitoru1=Algebra I course Enrollment in 8th Grade: All Students, total_alge1e=total_alge1e,total_grade8=total_grade8,total_enroll_alge1=total_enroll_alge1,cate=Enrolled); %saigo (taitoru2=Exhibit A-6 Algebra I,taitoru1=Algebra I course Enrollment in 8th Grade: Underrepresented Students, total_alge1e=ur_alge1e,total_grade8=ur_grade8,total_enroll_alge1=ur_enroll_alge1,cate=Enrolled); /* %saigo (taitoru2=,taitoru1=Algebra I course Completion in 8th Grade: All Students, total_alge1e=total_alge1c,total_grade8=total_grade8,total_enroll_alge1=total_compl_alge1); %saigo (taitoru2=,taitoru1=Algebra I course Completion in 8th Grade: Underrepresented Students, total_alge1e=ur_alge1c,total_grade8=ur_grade8,total_enroll_alge1=ur_compl_alge1); %saigo (taitoru2=,taitoru1=Higher-level Mathematics course Completion in 9-12th Grades: Underrepresented Students, total_alge1e=ur_himathc,total_grade8=ur_grade9to12,total_enroll_alge1=ur_compl_himath); %saigo (taitoru2=,taitoru1=Science course Completion in 9-12th Grades: Underrepresented Students, total_alge1e=ur_allscic,total_grade8=ur_grade9to12,total_enroll_alge1=ur_compl_allsci); */