Some colleges are more or less selective, so the baseline probability of admittance into each of the colleges is different. Predictors include student’s high school GPA, extracurricular activities, and SAT scores. Examples of mixed effects logistic regressionĮxample 1: A researcher sampled applications to 40 different colleges to study factors that predict admittance into college. In particular, it does not cover data cleaning and checking, verification of assumptions, model diagnostics or potential follow-up analyses. It does not cover all aspects of the research process which researchers are expected to do. Please note: The purpose of this page is to show how to use various data analysis commands. Mixed effects logistic regression is used to model binary outcome variables, in which the log odds of the outcomes are modeled as a linear combination of the predictor variables when data are clustered or there are both fixed and random effects. Version info: Code for this page was tested in Stata 12.1
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