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정렬법을 이용한 범주형 자료의 근사 측정동일성 분석

Analysis of Approximate Measurement Invariance of Categorical Indicators Using Alignment

장승민|주영신
한국심리학회 (The Korean Psychological Association)|2023.06|한국심리학회지:일반 (Korean Journal of Psychology: General)|제42권 제2호|pp. 119-140|DOI 10.22257/kjp.2023.6.42.2.119

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키워드

Alignmentmultiple group confirmatory factor analysis범주형 변수의 요인분석다집단 확인적 요인분석근사 측정동일성정렬법K-MMSEcategorical confirmatory factor analysisapproximate measurement invariance
주제분류심리과학

초록

요인모형을 이용한 측정동일성 분석에는 다집단 확인적 요인분석이 주로 사용되어왔다. 전통적인 관점에서는 측정동일성이 성립한다고 결론을 내리기 위해 비교 집단이나 시점 사이에 요인구조와 측정모수가 차이가 없이 완전히 동일하다는 근거가 필요하다. 그러나 집단의 수가 많은 경우 이와 같은 조건은 지나치게 엄격하거나 비현실적이 되기도 한다. 근사 측정동일성(approximate measurement invariance)은 비교 집단의 개수가 많을 때 이들 사이의 측정동일성을 현실적으로 검토하기 위해 제안된 완화된 형태의 측정동일성을 의미한다. 근사 측정동일성을 분석하는 주요 절차인 다집단 확인적 요인분석의 정렬법은 주로 연속형 측정변수에 대한 요인모형을 다수 국가 간에 비교하는 데 사용되어 왔다. 반면 연령에 따른 측정동일성의 분석은 주로 다집단 확인적 요인분석을 이용하여 둘 또는 셋으로 구분된 연령 집단을 비교하는 방식으로 수행되어 왔다. 그러나 연령에 따른 측정동일성의 분석에도 연령 집단을 세분한 다수의 연령 집단에 대해 근사측정동일성을 적용할 수 있다. 본 연구는 근사 측정동일성의 개념과 필요성, 분석 모형에 대해 논의하고 정렬법을 이용하여 심리검사의 연령에 따른 근사 측정동일성을 분석하는 방법과 절차를 예시하였다. 특히 범주형 자료에 대한 측정동일성 및 근사 측정동일성 분석에서의 개념적 유사점과 차이점을 논의하였으며 다집단 확인적 요인분석과 정렬법을 이용하여 인지기능 평가를 위한 검사인 K-MMSE 검사점수의 26개 연령 집단에 대한 측정동일성 및 근사 측정동일성을 분석하였다. 이를 통해 전통적인 측정동일성과 비교하여 근사 측정동일성 분석의 유용성을 강조하고 범주형 자료의 근사 측정동일성 분석과 관련된 논의사항들을 정리하였다.

Abstract

Multiple-group confirmatory factor analysis (CFA) has been widely used to analyze measurement equivalence using factor models. Traditionally, in order to conclude that measurement equivalence exists, it is necessary to have evidence that the factor structure and measurement parameters, such as factor loadings are completely identical, with no differences across target groups or measurement occasions. However, when the number of groups is large, these conditions can become overly stringent or impractical. Approximate measurement invariance is a relaxed form of measurement invariance and proposed to practically examine measurement invariance between many groups. Alignment is a widely used procedure for analyzing approximate measurement invariance and has been used to compare measurement models with continuous indicator between many countries. On the other hand, the analysis of measurement invariance of test scores across ages reflecting developmental changes in psychological attributes has been mainly conducted by comparing two or three small age groups using multiple-group CFA. However, in the analysis of measurement invariance across ages, approximate measurement invariance can be applied to ages that are divided into a large number of age groups. The current study discusses the idea, necessity, and analytical model of approximate measurement invariance and illustrates the analysis of the approximate measurement invariance of psychological tests over time using the alignment method. In particular, we discussed the conceptual similarities and differences between measurement invariance and approximate measurement invariance for factor models with categorical data, and introduced the analytical process of measurement invariance and approximate measurement invariance for 26 age groups of K-MMSE test scores, a test for assessing cognitive function, using multiple-group CFA and the alignment method. Based on the results of the analysis, the implications of approximate measurement invariance versus traditional measurement invariance were explained, and discussions related to analysis of approximate measurement invariance with categorical data were summarized.

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