Validity Generalization

The accumulation of external evidence of test validity becomes most important when test results are generalized across contexts, situations, and populations, and when the consequences of testing reach beyond the test's original intent. According to Messick (1995b), "The issue of generalizability of score inferences across tasks and contexts goes to the very heart of score meaning. Indeed, setting the boundaries of score meaning is precisely what generalizability evidence is meant to address" (p. 745).

Hunter and Schmidt (1990; Hunter, Schmidt, & Jackson, 1982; Schmidt & Hunter, 1977) developed a methodology of validity generalization, a form of meta-analysis, that analyzes the extent to which variation in test validity across studies is due to sampling error or other sources of error such as imperfect reliability, imperfect construct validity, range restriction, or artificial dichotomization. Once incongruent or conflictual findings across studies can be explained in terms of sources of error, meta-analysis enables theory to be tested, generalized, and quantitatively extended.

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