Exploratory Factor Analysis: Its Role in Item Analysis

TLDR

Exploratory factor analysis is challenged by item low reliability, unwanted covariance, and general factor issues, making default statistical package procedures inadequate, and it differs from cluster and confirmatory factor analysis. The study presents more appropriate procedures to mitigate these problems and guidance on sample selection, required sample size, and item selection for scales. The authors propose procedures that reduce factor analysis problems, provide guidelines for sample and item selection, and introduce a new evaluation method that uses factor correlations to avoid bias from total or factor scores. The default procedure yields too many factors and fails to detect a general factor, producing nonreplicable results.

Abstract

The special characteristics of items-low reliability, confounds by minor, unwanted covariance, and the likelihood of a general factor-and better understanding of factor analysis means that the default procedure of many statistical packages (Little Jiffy) is no longer adequate for exploratory item factor analysis. It produces too many factors and precludes a general factor even when that means the factors extracted are nonreplicable. More appropriate procedures that reduce these problems are presented, along with how to select the sample, sample size required, and how to select items for scales. Proposed scales can be evaluated by their correlations with the factors; a new procedure for doing so eliminates the biased values produced by correlating them with either total or factor scores. The role of exploratory factor analysis relative to cluster analysis and confirmatory factor analysis is noted.