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  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
  • 2024년 07월 03일(수) 13:30
 

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  • ENGLISH
  • P-ISSN1229-067X
  • E-ISSN2734-1127
  • KCI

이분형 종속변수를 포함하는 모형의 매개효과 검정

Testing the mediated effect of a model with a binary dependent variable

한국심리학회지: 일반 / Korean Journal of Psychology: General, (P)1229-067X; (E)2734-1127
2018, v.37 no.3, pp.441-470
https://doi.org/10.22257/kjp.2018.09.37.3.441
김수비 (이화여자대학교 심리학과)
김수영 (이화여자대학교)

초록

매개효과 모형은 심리학 등의 여러 사회과학 분야에서 가장 활발히 이용되는 분석 방법 중하나지만, 이분형 등의 범주형 종속변수를 포함하는 경우의 매개효과 검정 방법은 상대적으로 잘 알려져 있지 않다. 본 연구는 지난 30여 년간 이루어진 이분형 종속변수를 포함하는매개모형의 효과 추정 방법에 관한 연구 흐름들을 통합하고, 연구자들이 자신의 자료에 적합한 접근 방식을 선택할 수 있도록 핵심 쟁점들을 체계적으로 논의하는 것을 목적으로 한다. 이에 따라 이분형 종속변수를 포함하는 모형의 매개효과 추정 방법을 크게 두 가지 접근법으로 나누어 탐색한다. 먼저, 선형 구조방정식 모형을 비선형 모형으로 확장하는 전통적인 접근의 관점에서 이분형 종속변수를 포함하는 모형의 매개효과 추정 방법을 다룬다. 다음으로는 매개모형의 형태나 자료의 분포를 특정하지 않고 비모수적으로 매개효과를 추정하는 인과추론 접근법을 소개하고, 이를 이분형 종속변수를 포함하는 모형으로 확장한다. 그리고 통계 프로그램을 이용하여 전통적인 접근법과 인과추론 접근법을 실제자료에 적용한 예시를 보이며, 마지막으로 여러 결과를 종합하여 두 접근법의 원리 및 특징과 한계점 등을 논의한다.

keywords
binary dependent variable, non-linear model, mediation analysis, indirect effect, causal inference, 이분형 종속변수, 비선형 모형, 매개효과, 간접효과, 인과추론

Abstract

The mediational model is one of the most actively used analytical methods in the social sciences or psychology. However, the methods of testing the mediated effect with categorical dependent variables have been relatively unknown. The aims of the present study are to integrate studies on the methods of estimating the mediated effect of the model with a binary dependent variable over the last 30 years and to discuss key issues in order to encourage researchers to choose the most appropriate approach to their data. To achieve this goal, we explore the two streams of estimating the mediated effect of the model with a binary dependent variable, traditional vs. causal inference approaches. For the traditional approach,we introduce and integrate several extended structural equation modeling methods that accommodate a binary dependent variable in the mediational model. Then, we introduce the causal inference approach which allows researchers to estimate the mediated effect non-parametrically without specifying the form or distribution of the model before estimation, and extend it into a model that includes a binary dependent variable. Finally, we illustrate the procedures for applying the traditional and the causal inference approaches using real data and discuss the results.

keywords
binary dependent variable, non-linear model, mediation analysis, indirect effect, causal inference, 이분형 종속변수, 비선형 모형, 매개효과, 간접효과, 인과추론

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