범주형 확인적 요인분석 모형의 다집단 확장 = A multi-group analysis using the categorical confirmatory factor analysis

국문 초록 (Abstract)

범주형 확인적 요인분석은 심리학을 비롯한 사회과학 분야에서 빈번히 활용되는 범주형 변수(예, 리커트 척도 등)의 특성을 분석에 반영한 측정모형이다. 해당 모형의 다집단 확장에서 측정불변성을 확인하기 위해서는 단일 집단의 경우보다 모형 판별을 위하여 더 세분화된 척도화 및 제약이 수반되어야 하며, 측정불변성의 확인 단계 및 중요도 역시 연속형 지표변수를 상정한 경우와는 달라진다. 본 연구는 범주형 확인적 요인분석의 측정불변성과 관련하여 지금까지 이루어져 온 전체적인 논의를 탐색, 취합하여 연구자들이 자신의 연구 방향에 부합하는 판별 방식 및 측정불변성 확인 단계를 결정할 수 있도록 적절한 합의점을 도출하는 것을 목적으로 한다. 이를 위하여 두 가지 측면에서 논의가 이루어진다. 첫째, 모형의 판별 부분에서는 제한정보추정에 근거하여 두 종류의 잠재변수에 대한 척도화 및 다집단 분석을 위한 추가제약 방식을 다룬다. 둘째, 측정불변성 확인 단계에서는 범주형 지표변수를 상정하며 나타난 경계 모수의 동일성 확보를 중심으로 현재까지 제시되어 있는 측정불변성 확인 단계를 정리한다. 또한 앞서 제시된 판별 방식 및 측정불변성 확인 단계를 통계 프로그램을 이용하여 실제 자료 분석에 적용해 봄으로써 실질적인 활용을 도모한다. 마지막으로 판별 방식 및 측정불변성 확인 단계와 관련한 쟁점을 통합하여 각각의 상황에 부합하는 접근 방식의 특성 및 제한점을 논의한다.

다국어 초록 (Multilingual Abstract)

Categorical confirmatory factor analysis (CFA) is a measurement model that incorporates the categorical nature of the Likert scale, which is frequently used in the social sciences, including but not limited to psychology. The categorical CFA has quite different and complex model specification and identification as compared to the typical continuous CFA. A multi-group extension of the categorical CFA needs even more restrictions to be properly specified and identified. Moreover, the steps in checking the measurement invariance with the categorical indicator variables differ from those with the case of continuous indicator variables. The present study aims to help researchers choose proper methods and procedures for using a multi-group categorical CFA by investigating and integrating unorganized existing literature. To achieve this goal, we focus on two aspects. Based on the limited information estimation, we introduce scaling methods for the two types of latent variables, latent response variables and factors, and also address the method for parameter restrictions for multi-group analysis. Next, focusing on threshold parameters of the categorical CFA, we provide possible procedures for checking the measurement invariance. We then illustrate an application of the whole procedures using real data, and finally discuss the results.

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