Multilevel Structural Equation Models

Single level analyses are insufficient in studies consisting of many groups, when the degree of homogeneity is high among the individuals in these groups because of the violation of the assumption regarding the independence of observations. Multilevel analyses bring about many important advantages in the analyses of latent variables, by decomposing the variance at each level of the data in the hierarchical structure, thus enabling a simultaneous modeling. This study aims at introducing multilevel structural equation modeling, and presenting the researchers with an illustration of the analysis of empirical data gathered from a general ability test in line with this modeling. For this purpose, two-level structural equation modeling analysis has been performed to a data set of 381 observations nested in 39 classes by using the Mplus program. A model, in which a shared covariate and a measurement model exist with five indicators at both within and between levels, was tested, and the syntax of the related analyzed model was described. Finally, the findings of the analysis were discussed.