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Welcome to our research website. This site contains the results of our Monte Carlo simulation study that compares fit indices across robust estimation methods in multilevel confirmatory factor analysis (ML-CFA) models. There are few studies that have examined these complex models and even fewer that have focused on the performance of fit indices.

Below contains various pages for the different aspects of the project. The pages are broken up into what we considered logical sections of the results. Not all of the results shown here are reported in the manuscript. This limitation is mostly due to space restrictions in the actual manuscript.

Simulation Code

The following page displays the .txt and .R file used in the data generation and simulation study.

Fit Index Information

Below are links to pages that give more technical details on each of the fit indices investigatedin our study. We have tried to include much of the information that we could not include in the actual manuscript given the space limitations specified by the journal. Each page goes through the how the index designed and a basic description of what conclusion we expected for the utility of the index in multilevel settings.

*Comparative Fit Index (CFI)

*Comparative Fit Index (TLI)

*Root Mean Square Error of Approximation (RMSEA)

*Standardized Root Mean Square Residual (SRMR)

Estimation Method Technical Details

One downside of writing this article from a practicioner oriented perspective is that many of the technical details on estimation were severely glossed over in the actual manuscript. We know many readers of SEM will find interest in a deeper discussion of this part of the research which we did not dive deeply into in this paper. In the following pages, we will outline more of the technical details of each of the estimation methods chosen and discuss what potential benefits/limitations each has on the fit indices investigated. We try to treat this part as rigorously as possible, but understand that this is a very complex topic and we try to break down each estimation method to the major differences for discussion purposes.

*Maximum Likelihood (MLR)

*Weighted Least Squares Mean and Variance Adjusted (WLSMV)

*Unweighted Least Squares Mean and Variance Adjusted (ULSMV)