Enhancing predictive power by unamalgamating multi-item scales

The generally small but touted as "statistically significant" correlation coefficients in the social sciences jeopardize theory testing and prediction. To investigate these small coefficients' underlying causes, traditional equations such as Spearman's (1904) classic attenuation formula, Cronbach's (1951) alpha, and Guilford and Fruchter's (1973) equation for the effect of additional items on a scale's predictive power are considered. These equations' implications differ regarding large interitem correlations enhancing or diminishing predictive power. Contrary to conventional practice, such correlations decrease predictive power when treating items as multi-item scale components but can increase predictive power when treating items separately. The implications are wide-ranging. (PsycInfo Database Record (c) 2025 APA, all rights reserved).