MplusAutomation: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus.

Area of Science:

• Psychometrics
• Computational Statistics
• Structural Equation Modeling

Background:

• Complex latent variable analyses in Mplus can be labor-intensive.
• Managing numerous models and parameters poses a significant challenge.
• Efficient data extraction and comparison are crucial for robust findings.

Purpose of the Study:

• Introduce MplusAutomation, an R package designed to streamline Mplus analyses.
• Provide tools for creating and managing Mplus syntax for multiple models.
• Automate model estimation and facilitate the extraction and comparison of results.

Main Methods:

• Development of the MplusAutomation package in R.
• Utilizing applied examples to demonstrate package functionality.
• Conducting a large-scale simulation study to showcase capabilities.

Main Results:

• MplusAutomation effectively manages syntax for groups of related Mplus models.
• The package automates the estimation process for numerous models.
• Tools are provided for aggregating and comparing fit statistics and parameter estimates.

Conclusions:

• MplusAutomation reduces the effort required for large-scale latent variable analyses.
• The package supports methodological advancements in structural equation modeling.
• Facilitates efficient and comprehensive analysis within the Mplus environment.