OpenMx 2.0: Extended Structural Equation and Statistical Modeling
2015/01/26 by Michael C. Neale, Michael D. Hunter, Joshua N. Pritikin +7 · 1,185 citations
Decision Sciences · Mathematics · #Algorithm #Artificial intelligence #Computational statistics #Computer science #Data mining #Graphical user interface #Interface (matter) #LISREL #Machine learning #Modular design #Programming language #Psychometric Methodologies and Testing #Software #Statistical Methods and Applications #Statistical and numerical algorithms #Statistical model #Structural equation modeling #Syntax #Theoretical computer science
paper · open access · doi:10.1007/s11336-014-9435-8
published in Psychometrika 81(2), 535-549 (Springer Science+Business Media)
openalex publication_date 2015/01/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
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.
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