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Best Practices in Exploratory Factor Analysis for the Development of the Likert-type Scale

Abstract

Exploratory factor analysis (EFA) is a widely used analytical tool for development of psychological scales. Although guidelines for proper use of EFA have been proposed by many experts, special considerations for the item level factor analysis have been less emphasized. The current study highlighted that certain features of Likert-type items, such as low reliability and different levels of skewness, should be considered in EFA for scale development. The author suggested that a more than 5-point response scale is required for the common practice of EFA for the Likert-type scale development and, if not applicable, extraction of polychoric correlations is desirable, rather than Pearson correlations. Great emphasis has been placed on the use of parallel analysis and principle axis factoring or unweighted least squares method on polychoric correlations with oblique rotation. Higher item to factor ratio and larger sample size in comparison with scale level factor analysis are also emphasized. An EFA on the 10 items of the Rosenberg Self-Esteem Scale was illustrated with the proposed practices using the R statistical program.

keywords
탐색적 요인분석, 척도 개발, 리커트 문항 특성, R 프로그램, exploratory factor analysis, scale development, Likert item characteristics, R program

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