Analytic Standard Errors for Exploratory Process Factor Analysis

Guangjian Zhang (), Michael Browne, Anthony Ong and Sy Chow

Psychometrika, 2014, vol. 79, issue 3, 444-469

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. Copyright The Psychometric Society 2014

Keywords: factor analysis; time series analysis; standard error; dynamic factor analysis (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s11336-013-9365-x

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