Meta-Analytic Structural Equation Modeling with Fallible Measurements

Abstract

Meta-analytic structural equation modeling (MASEM) combines the strengths of meta-analysis with the flexibility of path models to address multivariate research questions using summary statistics. Because many research questions refer to latent constructs, measurement error can distort effect estimates in MASEMs if the unreliability of study variables is not properly acknowledged. Therefore, a comprehensive Monte Carlo simulation evaluated the impact of measurement error on MASEM results for different mediation models. These analyses showed that point estimates in MASEM were distorted by up to a third of the true effect, while confidence intervals exhibited undercoverage that were less than 10% in some situations. However, the use of adjustments for attenuation facilitated recovering largely undistorted point and interval estimates in MASEMs. These findings emphasize that MASEMs with fallible measurements can often yield highly distorted results. We encourage applied researchers to regularly adopt adjustment methods that account for attenuation in MASEMs.