Factor Loading Estimation Error and Stability Using Exploratory Factor Analysis

Exploratory factor analysis (EFA) is commonly employed to evaluate the factor structure of measures with dichotomously scored items. Generally, only the estimated factor loadings are provided with no reference to significance tests, confidence intervals, and/or estimated factor loading standard errors. This simulation study assessed factor loading estimation error under several experimental conditions and whether hypothesis testing and/or confidence intervals should be employed. Results revealed that the promax rotation performed well with small interfactor correlations and simple structure data, whereas varimax only performed well with orthogonal factors. Neither rotation method performed well with larger interfactor correlations or approximate simple structure data. An explanation of these results is provided.