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Related Experiment Video

Updated: Nov 30, 2025

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Comparing multiple statistical software for multiple-indicator, multiple-cause modeling: an application of gender

Chi Chang1,2, Joseph Gardiner3, Richard Houang4

  • 1Office of Medical Education Research and Development, College of Human Medicine, Michigan State University, 965 Wilson Rd., Room A214C, East Lansing, MI, 48824, USA. chisq@msu.edu.

BMC Medical Research Methodology
|November 13, 2020
PubMed
Summary

The multiple-indicator, multiple-cause (MIMIC) model, a latent variable framework, was applied using SAS, R, and Mplus to study cognitive function. Men excelled in executive function, while women showed better episodic memory.

Keywords:
Cognitive functioning performanceLatent variable frameworkMIDUS IIMIMIC modelMplusRSASStatistical software package comparisonStructural equation model

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Area of Science:

  • Psychometrics
  • Statistical Modeling
  • Cognitive Neuroscience

Background:

  • The multiple-indicator, multiple-cause (MIMIC) model is a specialized form of structural equation modeling (SEM) within a latent variable framework.
  • It integrates covariates of interest into factor analysis, offering rigorous results and broad availability in statistical software.

Purpose of the Study:

  • To introduce the multiple-indicator, multiple-cause (MIMIC) model.
  • To demonstrate its implementation using SAS CALIS, R lavaan, and Mplus.
  • To examine gender disparities in cognitive functioning using the MIMIC model.

Main Methods:

  • The study detailed the formulation, specification, and identification of the MIMIC model.
  • Empirical application involved the Midlife in the United States II (MIDUS II) Study dataset (N=4109).
  • Analyses were conducted using SAS CALIS procedure, R lavaan package, and Mplus version 8.0, presenting syntaxes for input, output, and diagrams.

Main Results:

  • All three software packages could utilize raw data and empirical covariance matrices.
  • Mplus offers greater modeling flexibility but limited data manipulation compared to SAS and R.
  • Results indicated men outperform women in executive function, while women exhibit superior episodic memory.

Conclusions:

  • The study validated the utility of the MIMIC model with three popular statistical software packages.
  • Findings align with previous empirical research on gender differences in cognitive functioning.
  • Coding procedures and examples are provided as a tutorial for researchers interested in latent construct modeling.