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Analytic Standard Errors for Exploratory Process Factor Analysis

Published online by Cambridge University Press:  01 January 2025

Guangjian Zhang ,
Michael W. Browne ,
Anthony D. Ong  and
Sy Miin Chow
Guangjian Zhang*
Affiliation:
University of Notre Dame
Michael W. Browne
Affiliation:
The Ohio State University
Anthony D. Ong
Affiliation:
Cornell University
Sy Miin Chow
Affiliation:
The Pennsylvania State University
*
Requests for reprints should be sent to Guangjian Zhang, Psychology Department, Haggar Hall, University of Notre Dame, Notre Dame, IN 46556, USA. E-mail: gzhang3@nd.edu
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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.

Keywords

factor analysistime series analysisstandard errordynamic factor analysis
Type
Original Paper
Information
Psychometrika , Volume 79 , Issue 3 , July 2014 , pp. 444 - 469
Copyright
Copyright © 2013 The Psychometric Society

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