The Korean Journal of Applied Statistics (2013) 26(6), 933–942 DOI: http://dx.doi.org/10.5351/KJAS.2013.26.6.933 A Comparative Study on Factor Recovery of Principal Component Analysis and Common Factor Analysis Sunho Jung a, 1 · Sangyun Seo a a School of Management, Kyung Hee University (Received August 23, 2013; Revised October 23, 2013; Accepted October 28, 2013) Abstract Common factor analysis and principal component analysis represent two technically distinctive approaches to exploratory factor analysis. Much of the psychometric literature recommends the use of common factor analysis instead of principal component analysis. Nonetheless, factor analysts use principal component analysis more frequently because they believe that principal component analysis could yield (relatively) less accurate estimates of factor loadings compared to common factor analysis but most often produce similar pattern of factor loadings, leading to essentially the same factor interpretations. A simulation study is conducted to evaluate the relative performance of these two approaches in terms of factor pattern recovery under different experimental conditions of sample size, overdetermination, and communality.The results show that principal component analysis performs better in factor recovery with small sample sizes (below 200). It was further shown that this tendency is more prominent when there are a small number of variables per factor. The present results are of practical use for factor analysts in the field of marketing and the social sciences. Keywords: Principle component analysis, common factor analysis, sample size, communality, overdetermi- nation, factor recovery. 1. 서론 탐색적 요인분석은 사회과학 연구에서 기본적인 분석도구로 사용되어 왔다 (Costello와 Osborne, 2005). 요인분석 사용자들은 탐색적 요인분석을 사용할 때 요인추출방법, 추출할 요인 수 결정, 요 인 축의 회전방법에 대해 단계적으로 의사결정을 한다. 그런데 각 단계에서 다양한 방법들이 존재하고 특정 방법의 선택에 따라 요인분석 결과가 달라질 수 있다. 이와 같은이유로 대표적인 요인추출방법 인 주성분분석과공통요인분석 중 어떤 방법을 선택해야 하는가에 대해 오랜 방법론적 논쟁이있어왔다 (Velicer과 Jackson, 1990). 다양한 측면에서 요인추출방법을 비교할 수 있지만 요인적재량 추정 능력면에서 보면 다음과같은 두 가 지 기준에서 평가할 수 있다 (Preacher과 MacCallum, 2002). 첫 번째 기준은 정확성 관점(precision perspective)에서 요인추출방법이 모수값(population values)에얼마나 가까운 추정치(parameter esti- mate)를 산출해 낼 수 있는가를 평가한다. 이 정확성 관점에서 수행된 연구들은 공통적으로 평균자승차 1 Corresponding author: Assistant Professor, School of Management, Kyung Hee University,1st Hoeigi-Dong, Dongdaemoon-gu, Seoul 130-701, Korea. E-mail: sunho.jung@khu.ac.kr