Conditional Process Analysis in Within-subjects designs: new opportunities with the memore macro

Abstract

Conditional process analysis is a statistical method which allows researchers to explore whether the mechanisms by which one variable affects another depend on moderator variables. These methods provide opportunities for deeper theory building in social psychology. However, these methods have been historically limited to between-subject designs. Social psychology commonly uses within-subject designs to support improved statistical power and external validity. The MEMORE macro for SPSS and SAS, introduced in 2017, provided an easy-to-use tool to estimate mediation and moderation separately. MEMORE provides a suite of options for inference for indirect effects including bootstrapping and Monte Carlo confidence intervals. The new version of MEMORE allows for 14 different conditional process models for within-subject designs, allowing for a single moderator on any combination of paths in models with one or more mediators. I will demonstrate how to use MEMORE to estimate conditional indirect effects and indices of moderated mediation. I will discuss reporting recommendations and recommendations for preregistration of analyses using MEMORE. I will overview functionality of the latest release and discuss future directions involving more complex models and outcome types.