Causal mediation analysis in nested case-control studies using conditional logistic regression

Research output: Contribution to journalJournal articleResearchpeer-review

  • Young Min Kim
  • John B. Cologne
  • Euna Jang
  • Lange, Theis
  • Yoshimi Tatsukawa
  • Waka Ohishi
  • Mai Utada
  • Harry M. Cullings

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.

Original languageEnglish
JournalBiometrical Journal
Issue number8
Pages (from-to)1939-1959
Number of pages21
Publication statusPublished - 2020

    Research areas

  • causal mediation analysis, cohort, conditional logistic regression, Cox proportional hazards model, nested case-control study, ATOMIC-BOMB SURVIVORS, BREAST-CANCER, RADIATION, IMPLEMENTATION, STATISTICS, EFFICIENCY, RISK

ID: 244648683