Comparison of Factor Retention Methods in Exploratory Factor Analysis: RMSEA, Root Deterioration per Restriction and Parallel Analysis

Abstract

The primary goal of exploratory factor analysis (EFA) is to determine the number of factors and their structure. Thus, the decision on the number of factors to retain is crucial. Nevertheless, researchers frequently overlook the precision of factor retention techniques and opt for unreliable methodologies instead. The objective of this study is to compare the efficiency of utilizing root mean square error of approximation (RMSEA) and parallel analysis (PA) methods for retaining factors in exploratory factor analysis (EFA). Two methods for comparing RMSEA, namely root deterioration per restriction (RDR) and RMSEA difference test, are employed for nested models. Although researchers use RMSEA to compare two different models, no studies have compared RMSEA and RDR methods. Thus, this study examined three different methods for factor retention. Monte-Carlo simulations were utilized to evaluate the accuracy of RDR compared to RMSEA difference testing and PA. The simulations show that RDR performs better than RMSEA difference testing and PA when the number of variables per factor is low. However, as the number of variables per factor increases, PA becomes more effective. This study provides guidance to researchers using EFA to select factor retention methods that suit different conditions.