OpenMx: An Open Source Extended Structural Equation Modeling Framework

By Steven M. Boker, Michael C. Neale, H. Maes, M. Wilde, Michael Spiegel, Timothy R. Brick, Jeffrey R. Spies, R. Estabrook, Sarah Kenny, Timothy C. Bates and 2 more. Psychometrika, 2011

1,168 citations recorded by the source corpus.

OpenMx is free, full-featured, open source, structural equation modeling (SEM) software. OpenMx runs within the R statistical programming environment on Windows, Mac OS–X, and Linux computers. The rationale for developing OpenMx is discussed along with the philosophy behind the user interface. The OpenMx data structures are introduced—these novel structures define the user interface framework and provide new opportunities for model specification. Two short example scripts for the specification and fitting of a confirmatory factor model are next presented. We end with an abbreviated list of modeling applications available in OpenMx 1.0 and a discussion of directions for future development.

Subfields: Food Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/8710c0118a1dbd7c2d89af66095a46d11b1e3f66

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Citations in the corpus

Qgraph: Network visualizations of relationships in psychometric data (2012, neutral): “SEM can be executed in R with three packages: sem (Fox 2006), OpenMx (Boker et al. 2011) and lavaan (Rosseel 2012).”
lavaan.survey: An R Package for Complex Survey Analysis of Structural Equation Models (2014, background): “None of the open-source SEM packages, sem (Fox 2006; Fox, Nie, and Byrnes 2012), openMx (Boker et al. 2011), and lavaan (Rosseel 2012), directly implement complex survey adjustments.”
Impact of Misspecifications of the Latent Variance–Covariance and Residual Matrices on the Class Enumeration Accuracy of Growth Mixture Models (2016, methodology): “E-mail: Alexandre.Morin@acu.edu.au Structural Equation Modeling: A Multidisciplinary Journal, 23: 507–531, 2016 Copyright © Taylor & Francis Group, LLC ISSN: 1070-5511 print / 1532-8007 online DOI: 10.1080/10705511.2016.1169188 Another reason for the increasing popularity of these models is the avai”
THE FAMILIAL RISK OF AUTISM (2014, neutral): “Age at ASD diagnosis 13 (4-22) 13 (4-22) 13 (4-23) 13 (4-22) 11 (4-21) 10 (4-25)”
Extending psychometric network analysis: Empirical evidence against g in favor of mutualism? (2019, methodology): “Per the recommendations in OpenMx (Boker et al., 2011), we obtained in our analyses: (1) The Non-normed Fit Index (NNFI), which represents the proportion of total covariance among the observed variables that is explained by a target model with the null model as a baseline model; (2) the Comparative ”
Affective Teacher–Student Relationships and Students' Engagement and Achievement: A Meta-Analytic Update and Test of the Mediating Role of Engagement (2017, methodology): “In Stage 1, the random effects approach is used as implemented in the R-package metaSEM (Cheung, 2014, 2015), which utilizes the OpenMx package (Boker et al., 2011) to pool the correlation coefficients.”
Assessing Mediation in Dyadic Data Using the Actor-Partner Interdependence Model (2011, methodology): “(This type of constraint can be directly imposed in programs like Mplus, OpenMx, or LISREL.)”
metaSEM: an R package for meta-analysis using structural equation modeling (2015, methodology): “This paper briefly outlines the theories and their implementations.”
Modeling dependent effect sizes with three-level meta-analyses: a structural equation modeling approach. (2014, methodology): “This section demonstrates how to conduct a three-level metaanalysis using the metaSEM package, that was based on the OpenMx package (Boker et al., 2011) for the R statistical environment (R Development Core Team, 2013).”
A checklist for testing measurement invariance (2012, background): “Lavaan (Rosseel, in press) and OpenMx (Boker et al., 2011) are both open-source R packages that are still being developed.”