Sample Size Limits for Estimating Upper Level Mediation Models Using Multilevel SEM

Abstract

This simulation study investigated use of the multilevel structural equation model (MLSEM) for handling measurement error in both mediator and outcome variables (M and Y) in an upper level multilevel mediation model. Mediation and outcome variable indicators were generated with measurement error. Parameter and standard error bias, confidence interval coverage, and power to detect the ab mediated effect using Empirical-M confidence interval estimates were assessed for the correct MLSEM versus a conventional multilevel model (MM) that used composite scores for M and Y. The following conditions were manipulated: level 1 and 2 sample sizes, intraclass correlation, degree of measurement error in M, and the true value of ab. The MLSEM more accurately recovered the ab effect's value, but serious convergence issues were encountered with MLSEM estimates based on fewer than 80 clusters. More power for detecting a nonzero ab was found for MM than for MLSEM estimates.