Explain the concept of differential prediction generalization.
What will be an ideal response?
Using their data, Aguinis et al. (2016) introduced the concept of differential prediction generalization. Specifically, they assessed the extent to which predicted first-year college GPA based on high-school grade point average and SAT scores depends on a student’s ethnicity and gender and whether this difference varies across samples. Similar to the need to take into account methodological and statistical artifacts in meta-analyses of validity coefficients in the context of differential validity research, they controlled for the effects of sample size, range restriction, proportion of students across ethnicity- and gender-based subgroups, subgroup mean differences on the predictors (i.e., HSGPA, SAT-Critical Reading, SAT-Math, and SAT-Writing), and SDs for the predictors. Although Mattern and Patterson (2013) reported the aggregated degree of differential prediction across all institutions combined, Aguinis et al.’s (2016) results at the institution level of analysis showed lack of differential prediction generalization.
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