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Mplus is a statistical modeling program that provides researchers with a flexible tool to analyze their data. Mplus offers researchers a wide choice of models, estimators, and algorithms in a program that has an easy-to-use interface and graphical displays of data and analysis results. Mplus allows the analysis of both cross-sectional and longitudinal data, single-level and multilevel data, data that come from different populations with either observed or unobserved heterogeneity, and data that contain missing values. Analyses can be carried out for observed variables that are continuous, censored, binary, ordered categorical (ordinal), unordered categorical (nominal), counts, or combinations of these variable types. In addition, Mplus has extensive capabilities for Monte Carlo simulation studies, where data can be generated and analyzed according to any of the models included in the program.
The Bayesian estimation is particularly valuable in cases with many latent variables where maximum-likelihood would be intractable due to too heavy numerical integration. The logit link for binary variables makes odds ratio interpretations available also with Bayes (Asparouhov & Muthén, 2020).
Timing tables for a variety of examples are presented in the technical documentation. (Download timing examples - i9-9900k, Proc=4).
Expanded and modified SRMR (Asparouhov & Muthén, 2018d)
Bivariate residual tests and factor score standard errors for the weighted least squares estimators
Cluster-specific plots for TWOLEVEL
Expanded odds ratio output
Standard errors for correlations with TYPE=BASIC using the H1SE option of the OUTPUT command
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