OpenMx 2.0: Extended Structural Equation and Statistical Modeling

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; Steven M. Boker

doi:10.1007/s11336-014-9435-8

OpenMx 2.0: Extended Structural Equation and Statistical Modeling

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, Steven M. Boker

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

603 Scopus citations

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.

Original language	English (US)
Pages (from-to)	535-549
Number of pages	15
Journal	Psychometrika
Volume	81
Issue number	2
DOIs	https://doi.org/10.1007/s11336-014-9435-8
State	Published - Jun 1 2016

Keywords

behavior genetics
big data
full information maximum likelihood
item factor analysis
latent class analysis
mixture distribution
optimization
ordinal data
path analysis
state space modeling
structural equation modeling
substance use data analysis
time series

ASJC Scopus subject areas

Psychology(all)
Applied Mathematics

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10.1007/s11336-014-9435-8

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title = "OpenMx 2.0: Extended Structural Equation and Statistical Modeling",

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 = "behavior genetics, big data, full information maximum likelihood, item factor analysis, latent class analysis, mixture distribution, optimization, ordinal data, path analysis, state space modeling, structural equation modeling, substance use data analysis, time series",

author = "Neale, {Michael C.} and Hunter, {Michael D.} and Pritikin, {Joshua N.} and Mahsa Zahery and Brick, {Timothy R.} and Kirkpatrick, {Robert M.} and Ryne Estabrook and Bates, {Timothy C.} and Maes, {Hermine H.} and Boker, {Steven M.}",

note = "Funding Information: The authors gratefully acknowledge funding from the National Institutes of Health, specifically Grants R01-DA022989 (PI Boker), R37-DA018673 and R25-DA026119 (PI Neale). Thanks are also due to a large group of beta-testers, including but not limited to: Mike W.-L. Cheung (), Charles Driver, Dorothy Bishop, Greg Carey, Pascal Deboeck, Emilio Ferrer, Christopher Hertzog, Kevin Grimm, Ken Kelley, Matthew Keller, Jean-Philippe Laurenceau, Gitta Lubke, John J. McArdle, Sam McQuillin, Sarah Medland, William Revelle, Michael Scharkow, James Steiger, Melissa Sturge-Apple, and Theodore Walls. Publisher Copyright: {\textcopyright} 2015, The Psychometric Society.",

year = "2016",

month = jun,

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doi = "10.1007/s11336-014-9435-8",

language = "English (US)",

volume = "81",

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AU - Neale, Michael C.

AU - Hunter, Michael D.

AU - Pritikin, Joshua N.

AU - Zahery, Mahsa

AU - Brick, Timothy R.

AU - Kirkpatrick, Robert M.

AU - Estabrook, Ryne

AU - Bates, Timothy C.

AU - Maes, Hermine H.

AU - Boker, Steven M.

N1 - Funding Information: The authors gratefully acknowledge funding from the National Institutes of Health, specifically Grants R01-DA022989 (PI Boker), R37-DA018673 and R25-DA026119 (PI Neale). Thanks are also due to a large group of beta-testers, including but not limited to: Mike W.-L. Cheung (), Charles Driver, Dorothy Bishop, Greg Carey, Pascal Deboeck, Emilio Ferrer, Christopher Hertzog, Kevin Grimm, Ken Kelley, Matthew Keller, Jean-Philippe Laurenceau, Gitta Lubke, John J. McArdle, Sam McQuillin, Sarah Medland, William Revelle, Michael Scharkow, James Steiger, Melissa Sturge-Apple, and Theodore Walls. Publisher Copyright: © 2015, The Psychometric Society.

PY - 2016/6/1

Y1 - 2016/6/1

N2 - 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.

AB - 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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KW - big data

KW - full information maximum likelihood

KW - item factor analysis

KW - latent class analysis

KW - mixture distribution

KW - optimization

KW - ordinal data

KW - path analysis

KW - state space modeling

KW - structural equation modeling

KW - substance use data analysis

KW - time series

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JO - Psychometrika

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ER -

OpenMx 2.0: Extended Structural Equation and Statistical Modeling

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