OpenMx: an open source extended structural equation modeling framework. 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.

References in zbMATH (referenced in 16 articles , 2 standard articles )

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  1. Charles Driver and Johan Oud and Manuel Voelkle: Continuous Time Structural Equation Modeling with R Package ctsem (2017)
  2. Epskamp, Sacha; Rhemtulla, Mijke; Borsboom, Denny: Generalized network psychometrics: combining network and latent variable models (2017)
  3. Nora Umbach and Katharina Naumann and Holger Brandt and Augustin Kelava: Fitting Nonlinear Structural Equation Models in R with Package nlsem (2017)
  4. de Zeeuw, Eveline L.; van Beijsterveldt, Catharina E.M.; Glasner, Tina J.; de Geus, Eco J.C.; Boomsma, Dorret I.: Arithmetic, reading and writing performance has a strong genetic component: a study in primary school children (2016) MathEduc
  5. Neale, Michael C.; Hunter, Michael D.; Pritikin, Joshua N.; Zahery, Mahsa; Brick, Timothy R.; Kirkpatrick, Robert M.; Estabrook, Ryne; Bates, Timothy C.; Maes, Hermine H.; Boker, Steven M.: OpenMX 2.0: extended structural equation and statistical modeling (2016)
  6. Wu, Hao; Estabrook, Ryne: Identification of confirmatory factor analysis models of different levels of invariance for ordered categorical outcomes (2016)
  7. Pek, Jolynn; Wu, Hao: Profile likelihood-based confidence intervals and regions for structural equation models (2015)
  8. Duy, Truong Vinh Truong; Ozaki, Taisuke: A decomposition method with minimum communication amount for parallelization of multi-dimensional FFTs (2014)
  9. Chow, Sy-Miin; Zhang, Guangjian: Nonlinear regime-switching state-space (RSSS) models (2013)
  10. Holst, Klaus Kähler; Budtz-Jørgensen, Esben: Linear latent variable models: the lava-package (2013)
  11. Merkle, Edgar C.; Zeileis, Achim: Tests of measurement invariance without subgroups: a generalization of classical methods (2013)
  12. Wollschläger, Daniel: R compact. The fast introduction into data analysis (2013)
  13. Wu, Hao; Neale, Michael C.: On the likelihood ratio tests in bivariate ACDE models (2013)
  14. Boker, Steven; Neale, Michael; Maes, Hermine; Wilde, Michael; Spiegel, Michael; Brick, Timothy; Spies, Jeffrey; Estabrook, Ryne; Kenny, Sarah; Bates, Timothy; Mehta, Paras; Fox, John: OpenMx: an open source extended structural equation modeling framework (2011)
  15. Wilde, Michael; Hategan, Mihael; Wozniak, Justin M.; Clifford, Ben; Katz, Daniel S.; Foster, Ian: Swift: A language for distributed parallel scripting (2011) ioport
  16. Nakayama, Hiromasa: An interactive user interface for division algorithms and the Buchberger algorithm (2006)