Correcting for bias due to mismeasured exposure in mediation analysis with a survival outcome
We investigate the impact of exposure measurement error on assessing mediation with a survival outcome modelled by Cox regression. We first derive the bias formulas of natural indirect and direct effects with a rare outcome and no exposure-mediator interaction. We then develop several calibration approaches to correct for the measurement error-induced bias, and generalize our methods to accommodate a common outcome and an exposure-mediator interaction. We apply the proposed methods to analyse the Health Professionals Follow-up Study (1986-2016) and evaluate the extent to which reduced body mass index mediates the protective effect of physical activity on risk of cardiovascular diseases.
Authors
- Donna Spiegelman (ORCID: https://orcid.org/0000-0003-4006-4650)
- Fan Li (ORCID: https://orcid.org/0000-0001-6183-1893)
- Chao Cheng (ORCID: https://orcid.org/0000-0003-3234-5874)
Institutions
- Yale University (US)
Publication Details
- Journal
- Journal of the Royal Statistical Society Series C (Applied Statistics)
- Published
- 2025-01-28
- DOI
- https://doi.org/10.1093/jrsssc/qlaf010
- Primary Topic
- Advanced Causal Inference Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Patient-Centered Outcomes Research Institute
- National Institutes of Health