A Sandwich Standard Error Estimator for Exploratory Factor Analysis With Nonnormal Data and Imperfect Models. Issue 5 (July 2019)

• Record Type: Journal Article
• Authors: Zhang, Guangjian; Preacher, Kristopher J.; Hattori, Minami; Jiang, Ge; Trichtinger, Lauren A.
• Is Part Of: Applied psychological measurement. Volume 43:Issue 5(2019)
• Page Start: 360
• Page End: 373
• Publication Date: 2019-07
• Subjects: factor analysis -- latent variable models -- factor rotation -- standard errors; Psychometrics -- Periodicals; Psychological tests -- Periodicals; Psychology, Applied -- Periodicals; 150.1519505
• DOI: 10.1177/0146621618798669
• Languages: English
• ISSNs: 0146-6216

Abstract

This article is concerned with standard errors ( SE s) and confidence intervals (CIs) for exploratory factor analysis (EFA) in different situations. The authors adapt a sandwich SE estimator for EFA parameters to accommodate nonnormal data and imperfect models, factor extraction with maximum likelihood and ordinary least squares, and factor rotation with CF-varimax, CF-quartimax, geomin, or target rotation. They illustrate the sandwich SE s and CIs using nonnormal continuous data and ordinal data. They also compare SE estimates and CIs of the conventional information method, the sandwich method, and the bootstrap method using simulated data. The sandwich method and the bootstrap method are more satisfactory than the information method for EFA with nonnormal data and model approximation error.