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Causal mediation analysis in nested case-control studies using conditional logistic regression
Authors:Young Min Kim  John B. Cologne  Euna Jang  Theis Lange  Yoshimi Tatsukawa  Waka Ohishi  Mai Utada  Harry M. Cullings
Affiliation:1. Department of Statistics, Kyungpook National University, 80 Daehak-ro, Daegu, Republic of Korea;2. Department of Statistics, Radiation Effects Research Foundation, Hiroshima, Hiroshima Prefecture, Japan;3. Section of Biostatistics, University of Copenhagen, Copenhagen, Denmark;4. Department of Clinical Studies, Radiation Effects Research Foundation, Hiroshima, Hiroshima Prefecture, Japan;5. Department of Epidemiology, Radiation Effects Research Foundation, Hiroshima, Hiroshima Prefecture, Japan
Abstract:The paper proposes an approach to causal mediation analysis in nested case-control study designs, often incorporated with countermatching schemes using conditional likelihood, and we compare the method's performance to that of mediation analysis using the Cox model for the full cohort with a continuous or dichotomous mediator. Simulation studies are conducted to assess our proposed method and investigate the efficiency relative to the cohort. We illustrate the method using actual data from two studies of potential mediation of radiation risk conducted within the Adult Health Study cohort of atomic-bomb survivors. The performance becomes comparable to that based on the full cohort, illustrating the potential for valid mediation analysis based on the reduced data obtained through the nested case-control design.
Keywords:causal mediation analysis  cohort  conditional logistic regression  Cox proportional hazards model  nested case-control study
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