How to understand and test statistical interaction effect

Using the regression model framework, an analyst can test whether the effect of X depends on another predictor.  If the outcome is student achievement and the most important independent variable is the intervention variable (students received treatment 1; else 0), one can further ask if the program effect depends on students’ demographic factors, such as gender, race and ethnicity, and some important student statues (e.g., special education, English learner).  If the main research question is whether the program has an effect on student outcome, we often ask the next question, “does the program effect depend on student demographic factors or student status variables.  If, for example, an educational intervention program works only for boys but not for girls, we expect to see statistical interaction between intervention and gender.  You can say this in different ways:

  1. The program impact varies by gender
  2. The effect of the program depends on gender
  3. The program and gender interact
  4. Gosh, this program is effective particularly for boys!

I will continue to use gender as an example through this text.

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How to test and understand statistical interaction effect

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