Abstract
Meta-analytic structural equation modeling (MASEM) is a statistical technique to pool correlation matrices and test structural equation models on the pooled correlation matrix. In Stage 1 of MASEM, correlation matrices from independent studies are combined to obtain a pooled correlation matrix, using fixed- or random-effects analysis. In Stage 2, a structural model is fitted to the pooled correlation matrix. Researchers applying MASEM may have hypotheses about how certain model parameters will differ across subgroups of studies. These moderator hypotheses are often addressed using suboptimal methods. The aim of the current article is to provide guidance and examples on how to test hypotheses about group differences in specific model parameters in MASEM. We illustrate the procedure using both fixed- and random-effects subgroup analysis with two real datasets. In addition, we present a small simulation study to evaluate the effect of the number of studies per subgroup on convergence problems. All data and the R-scripts for the examples are provided online.
Highlights
The Hospital Anxiety and Depression Scale (HADS) was designed to measure psychological distress in non-psychiatric patient populations (Zigmond & Snaith, 1983), and is widely used in research on distress in patients
We focus on two-stage SEM (TSSEM), in which subgroup analysis is the only option to evaluate moderator effects
In order to illustrate the modeling involved in Case 1, we will continue with Stage 2 using overall fixedeffects analysis
Summary
The HADS was designed to measure psychological distress in non-psychiatric patient populations (Zigmond & Snaith, 1983), and is widely used in research on distress in patients. The instrument consists of 14 items: the odd numbered items are designed to measure anxiety and the even numbered items are designed to measure depression. The items are scored on a 4-point scale. Some controversy exists regarding the validity of the HADS (Zakrzewska, 2012). The HADS has generally been found to be a useful instrument for screening purposes, but not for diagnostics purposes (Mitchell, Meader, & Symonds, 2010). Ambiguous results regarding the factor structure of the HADS led to a meta-analytic study by Norton et al (2013), who gathered correlation matrices of the 14 HADS items from 28
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