Archive for November, 2014

OpenMx 2.0: Extended Structural Equation and Statistical Modeling

Thursday, November 6th, 2014

Neale, M.C., Hunter, M.D., Pritikin, J.N., Zahery, M., Brick, T.R., Kirkpatrick, R., Estabrook, R., Bates, T.C., Maes, H.H., & Boker, S.M.; (in press) OpenMx 2.0: Extended Structural Equation and Statistical Modeling. Psychometrika

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 (IRT) 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.

The manuscript of this article accepted for publication can be downloaded as a PDF. This article may not exactly replicate the final version published in Psychometrika. It is not the copy of record.

Modular Open-Source Software for Item Factor Analysis

Wednesday, November 5th, 2014

Pritikin, J. N., Hunter, M. D., & Boker, S. M. (2015) Modular Open-Source Software for Item Factor Analysis. Educational and Psychological Measurement 75:(3), 458-474

This paper introduces an Item Factor Analysis (IFA) module for OpenMx, a free, open-source, and modular statistical modeling package that runs within the R programming environment on GNU/Linux, Mac OS X, and Microsoft Windows. The IFA module offers a novel model specification language that is well suited to programmatic generation and manipulation of models. Modular organization of the source code facilitates the easy addition of item models, item parameter estimation algorithms, optimizers, test scoring algorithms, and fit diagnostics all within an integrated framework. Three short example scripts are pre- sented for fitting item parameters, latent distribution parameters, and a multiple group model. The availability of both IFA and structural equation modeling in the same software is a step toward the unification of these two methodologies.

The manuscript of this article accepted for publication can be downloaded as a PDF. This article may not exactly replicate the final version published in Educational and Psychological Measurement. It is not the copy of record.