지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2024.1
- 수록면
- 161 - 177 (17page)
- DOI
- 10.7465/jkdi.2024.35.1.161
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초록· 키워드
오류제보하기
Observational studies encounter self-selection bias due to non-randomized treatment assignments. To solve the problem of the self-selection bias, we employ the propensity score matching approach to compare non-randomized treatment and control groups and estimate the robust marginal treatment effect. In this study, we consider the double-adjustment and g-computation methods to reduce residual confounding bias, target bias, and propensity score model bias, and the caliper method to address the confounding bias. We compute the robust marginal causal effect of smoking on depressive symptoms to investigate the relationship between smoking and depressive symptoms using the 8<SUP>th</SUP> Korean National Health and Nutrition Examination Survey dat.
목차
Abstract
1. Introduction
2. Propensity score matching
3. Robust estimaiton of marginal treatment effects
4. Data application with Korea National Health and Nutrition Examination Survey
5. Discussion and Conclusion
References
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