The tradeoff between accuracy and precision in latent variable models of mediation processes

摘要

Social psychologists place high importance on understanding mechanisms, and frequently employ mediation analyses to shed light on the process underlying an effect. Such analyses can be conducted using observed variables (e.g., a typical regression approach) or latent variables (e.g., a SEM approach), and choosing between these methods can be a more complex and consequential decision than researchers often realize. The present paper adds to the literature on mediation by examining the relative tradeoff between accuracy and precision in latent versus observed variable modeling. Whereas past work has shown that latent variable models tend to produce more accurate estimates, we demonstrate that observed variable models tend to produce more precise estimates, and examine this relative tradeoff both theoretically and empirically in a typical three-variable mediation model across varying levels of effect size and reliability. We discuss implications for social psychologists seeking to uncover mediating variables, and recommend practical approaches for maximizing both accuracy and precision in mediation analyses.