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Yang, Ji Seung; Zheng, Xiaying – Journal of Educational and Behavioral Statistics, 2018
The purpose of this article is to introduce and review the capability and performance of the Stata item response theory (IRT) package that is available from Stata v.14, 2015. Using a simulated data set and a publicly available item response data set extracted from Programme of International Student Assessment, we review the IRT package from…
Descriptors: Item Response Theory, Item Analysis, Computer Software, Statistical Analysis
Jeon, Minjeong; Rabe-Hesketh, Sophia – Journal of Educational and Behavioral Statistics, 2012
In this article, the authors suggest a profile-likelihood approach for estimating complex models by maximum likelihood (ML) using standard software and minimal programming. The method works whenever setting some of the parameters of the model to known constants turns the model into a standard model. An important class of models that can be…
Descriptors: Maximum Likelihood Statistics, Computation, Models, Factor Structure
Lee, Sik-Yum; Song, Xin-Yuan; Lee, John C. K. – Journal of Educational and Behavioral Statistics, 2003
The existing maximum likelihood theory and its computer software in structural equation modeling are established on the basis of linear relationships among latent variables with fully observed data. However, in social and behavioral sciences, nonlinear relationships among the latent variables are important for establishing more meaningful models…
Descriptors: Structural Equation Models, Simulation, Computer Software, Computation