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Korean Journal of Psychology: General

Bifactor Modeling Approach to Investigate Studying of Psychometric Properties of Psychological Measures

Korean Journal of Psychology: General / Korean Journal of Psychology: General, (P)1229-067X; (E)2734-1127
2017, v.36 no.4, pp.477-504
https://doi.org/10.22257/kjp.2017.09.36.3.477


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Abstract

Bifactor modeling approach is increasingly being applied to the study of psychometric properties of psychological measures. A bifactor structure consists of a single general factor that is purported to explain co-variances of all the items and a set of group factors that are purported to explain residual co-variances of some items that cannot be accounted for by a general factor. The model assumes that the general and group factors are uncorrelated. Bifactor modeling approach enables researchers to test whether a given psychological scale that is originally designed to measure a theoretically unidimensional construct appears to be multidimensional due to nuisance factors such as method factors. In this article, we gave an overview of statistical indices such as omega coefficients and explained common variance(ECV) that can be effectively employed to investigate dimensionality of a given scale. We illustrated how to compute various types of omega coefficients and explained common variance(ECV) and interpret them using Rosenberg Self-esteem scale(RSES) and Emotional Approach Coping Scale(EAC).

keywords
쌍요인 모형, 일반요인, 집단요인, 오메가 계수, 일차원 지수(ECV), 확인적 요인분석, Bifactor model, general factor, group factor, omega coefficients, ECV, confirmatory factor analysis

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Korean Journal of Psychology: General