Members enter groups with different characteristics, for example, gender and ethnicity, and the Group Actor–Partner Interdependence Model (GAPIM) systematically tests several different effects of group composition for a given characteristic. By finding submodels of these effects, the GAPIM allows for empirically testing many theoretically meaningful models of differences within groups. Among the models that can be tested are models of diversity, relational demography, group norms, and contrast. This paper describes the four different steps of a GAPIM analysis and illustrates its application with two datasets. The first is an experimental dataset where gender composition is manipulated by presenting individuals with pictures of group members with whom they presumably would interact. The second dataset is a national sample of churchgoers who are members of different congregations, in which the effects of both a categorical and a continuous composition variable on a member-level outcome are assessed. SPSS and R syntax used for running the GAPIM is provided for each of these examples.
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