Six Methods for Latent Moderation Analysis in Marketing Research: A Comparison and Guidelines

Abstract

It is common in moderation analysis that at least one of the target moderation variables is latent and measured with measurement error. This article compares six methods for latent moderation analysis: multigroup, means, corrected means, factor scores, product indicators, and latent product. It reviews their use in marketing research, describes their assumptions, and compares their performance with Monte Carlo simulations. Several recommendations follow from the results. First, although the means method is the most frequently used method in the review (95% of articles), it should only be used when reliabilities of the moderation variables are close to 1, which is rare. Then, all methods except the multigroup method perform similarly well. Second, the results support using the factor scores method and latent product method when reliabilities are smaller than 1. These methods perform best with parameter and standard error bias less than or equal to 5% under most investigated conditions. Third, specific settings can warrant using the multigroup method (if the moderator is discrete), the corrected means method (if moderation variables are single indicators), and the product indicators method (if indicators are nonnormally distributed). Practical guidelines and sample code for four statistical platforms (SPSS, Stata, R, and Mplus) are provided.