Validation and statistical power: Implications for applied research

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Comments that criterion-related validity studies are often not technically feasible because sample sizes are inadequate for necessary statistical power (e.g., .90). Effect sizes are frequently overestimated because of a failure to consider the combined effects of range restriction and criterion unreliability, both of which attenuate validity coefficients. Restricted validities must therefore be estimated by applying appropriate correction formulas. In this study the corrections are made for the multiple prediction case. Required sample sizes, determined using the univariate power model, are presented for a range of unit-weighted predictors, for varying degrees of restriction, and for power levels of .50 and .90. The advantage of multiple predictors is shown by comparing their required sample size to that of the best single predictor. For a given power, effect size is clearly the major determinant of required sample size. Implications for applied research are discussed. (13 ref) (PsycINFO Database Record (c) 2006 APA, all rights reserved)

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