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OpenMx 2.0: Extended Structural Equation and Statistical Modeling

Published online by Cambridge University Press:  01 January 2025

Michael C. Neale ,
Michael D. Hunter ,
Joshua N. Pritikin ,
Mahsa Zahery ,
Timothy R. Brick ,
Robert M. Kirkpatrick ,
Ryne Estabrook ,
Timothy C. Bates ,
Hermine H. Maes  and
Steven M. Boker
Michael C. Neale*
Affiliation:
Virginia Commonwealth University
Michael D. Hunter
Affiliation:
University of Oklahoma
Joshua N. Pritikin
Affiliation:
University of Virginia
Mahsa Zahery
Affiliation:
Virginia Commonwealth University
Timothy R. Brick
Affiliation:
Pennsylvania State University
Robert M. Kirkpatrick
Affiliation:
Virginia Commonwealth University
Ryne Estabrook
Affiliation:
Northwestern University
Timothy C. Bates
Affiliation:
University of Edinburgh
Hermine H. Maes
Affiliation:
Virginia Commonwealth University
Steven M. Boker
Affiliation:
University of Virginia
*
Correspondence should be made to Michael C. Neale, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, USA. Email: [email protected]
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Abstract

The new software package OpenMx 2.0 for structural equation and other statistical modeling is introduced and its features are described. OpenMx is evolving in a modular direction and now allows a mix-and-match computational approach that separates model expectations from fit functions and optimizers. Major backend architectural improvements include a move to swappable open-source optimizers such as the newly written CSOLNP. Entire new methodologies such as item factor analysis and state space modeling have been implemented. New model expectation functions including support for the expression of models in LISREL syntax and a simplified multigroup expectation function are available. Ease-of-use improvements include helper functions to standardize model parameters and compute their Jacobian-based standard errors, access to model components through standard R $ mechanisms, and improved tab completion from within the R Graphical User Interface.

Keywords

structural equation modelingpath analysisitem factor analysisstate space modelingmixture distributionlatent class analysisoptimizationbig datatime seriesbehavior geneticssubstance use data analysisfull information maximum likelihoodordinal data
Type
Article
Information
Psychometrika , Volume 81 , Issue 2 , June 2016 , pp. 535 - 549
Copyright
Copyright © 2015 The Psychometric Society

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