Bootstrap Confidence Intervals for Ordinary Least Squares Factor Loadings and Correlations in Exploratory Factor Analysis

Multivariate Behavioral Research
Guangjian ZhangShanhong Luo

Abstract

This article is concerned with using the bootstrap to assign confidence intervals for rotated factor loadings and factor correlations in ordinary least squares exploratory factor analysis. Coverage performances of SE-based intervals, percentile intervals, bias-corrected percentile intervals, bias-corrected accelerated percentile intervals, and hybrid intervals are explored using simulation studies involving different sample sizes, perfect and imperfect models, and normal and elliptical data. The bootstrap confidence intervals are also illustrated using a personality data set of 537 Chinese men. The results suggest that the bootstrap is an effective method for assigning confidence intervals at moderately large sample sizes.

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Citations

May 28, 2010·Multivariate Behavioral Research·Guangjian Zhang, Michael W Browne
Mar 30, 2012·Multivariate Behavioral Research·Chun-Ting LeeMichael C Edwards
Nov 1, 2012·Multivariate Behavioral Research·Stanislav StakhovychMichel Wedel
Feb 5, 2014·Psychometrika·Guangjian ZhangSy Miin Chow
Jan 15, 2014·International Journal of Audiology·Michael A AkeroydSharon L Suller
May 29, 2012·European Journal of Cancer : Official Journal for European Organization for Research and Treatment of Cancer (EORTC) [and] European Association for Cancer Research (EACR)·Doris HowellLisa Barbera
Jul 1, 2014·Multivariate Behavioral Research·Guangjian Zhang
Mar 15, 2018·Annals of Behavioral Medicine : a Publication of the Society of Behavioral Medicine·Natalie O RosenSophie Bergeron
Jun 14, 2019·Veterinary Medicine International·Jaimie M StricklandJohn P Buchweitz
Aug 9, 2020·Multivariate Behavioral Research·Allison W Cooperman, Niels Waller
Jun 12, 2021·Journal of Clinical Psychology·Pablo E Flores-KanterLeonardo A Medrano

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Software Mentioned

EFA
R
CEFA
Fortran

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