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Analytic Standard Errors for Exploratory Process Factor Analysis |
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| Authors: | Guangjian Zhang Michael W. Browne Anthony D. Ong Sy Miin Chow |
| Affiliation: | 1. Psychology Department, Haggar Hall, University of Notre Dame, Notre Dame, IN, 46556, USA 2. The Ohio State University, Columbus, USA 3. Cornell University, Ithaca, USA 4. The Pennsylvania State University, University Park, USA |
| Abstract: | Exploratory process factor analysis (EPFA) is a data-driven latent variable model for multivariate time series. This article presents analytic standard errors for EPFA. Unlike standard errors for exploratory factor analysis with independent data, the analytic standard errors for EPFA take into account the time dependency in time series data. In addition, factor rotation is treated as the imposition of equality constraints on model parameters. Properties of the analytic standard errors are demonstrated using empirical and simulated data. |
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