A Sandwich Standard Error Estimator for Exploratory Factor Analysis With Nonnormal Data and Imperfect Models

Guangjian Zhang, Kristopher J. Preacher, Minami Hattori, Ge Jiang, Lauren A. Trichtinger

Research output: Contribution to journalArticlepeer-review

Abstract

This article is concerned with standard errors (SEs) 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 SEs 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.
Original languageEnglish (US)
Pages (from-to)360-373
Number of pages14
JournalApplied Psychological Measurement
Volume43
Issue number5
Early online dateSep 14 2018
DOIs
StatePublished - Jul 1 2019

Keywords

  • factor analysis
  • factor rotation
  • latent variable models
  • standard errors

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Psychology (miscellaneous)

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