Nesting Monte Carlo EM for high-dimensional item factor analysis |
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| Authors: | Xinming An Peter M Bentler |
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| Institution: | 1. Department of Psychology , University of California , 1285 Franz Hall, Box 951563, Los Angeles , CA , USA;2. Department of Psychology and Statistics , University of California , 1285 Franz Hall, Box 951563, Los Angeles , CA , USA |
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| Abstract: | The item factor analysis model for investigating multidimensional latent spaces has proved to be useful. Parameter estimation in this model requires computationally demanding high-dimensional integrations. While several approaches to approximate such integrations have been proposed, they suffer various computational difficulties. This paper proposes a Nesting Monte Carlo Expectation-Maximization (MCEM) algorithm for item factor analysis with binary data. Simulation studies and a real data example suggest that the Nesting MCEM approach can significantly improve computational efficiency while also enjoying the good properties of stable convergence and easy implementation. |
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| Keywords: | full information item factor analysis Monte Carlo EM nesting EM |
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