Estimating Heterogeneous Exposure Effects in the Case-Crossover Design Using BART
成果类型:
Article
署名作者:
Englert, Jacob R.; Ebelt, Stefanie T.; Chang, Howard H.
署名单位:
Emory University; Rollins School Public Health; Emory University
刊物名称:
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
ISSN/ISSBN:
0162-1459; 1537-274X
DOI:
10.1080/01621459.2025.2460231
发表日期:
2025-07-03
页码:
1335-1346
关键词:
Alzheimer's disease
Bayesian additive regression trees
Environmental epidemiology
CORE-BODY-TEMPERATURE
Hospital admissions
alzheimers-disease
mortality
california
extremes
rhythms
city
摘要:
Epidemiological approaches for examining human health responses to environmental exposures in observational studies often control for confounding by implementing clever matching schemes and using statistical methods based on conditional likelihood. Nonparametric regression models have surged in popularity in recent years as a tool for estimating individual-level heterogeneous effects, which provide a more detailed picture of the exposure-response relationship but can also be aggregated to obtain improved marginal estimates at the population level. In this work we incorporate Bayesian additive regression trees (BART) into the conditional logistic regression model to identify heterogeneous exposure effects in a case-crossover design. Conditional logistic BART (CL-BART) uses reversible jump Markov chain Monte Carlo to bypass the conditional conjugacy requirement of the original BART algorithm. Our work is motivated by the growing interest in identifying subpopulations more vulnerable to environmental exposures. We apply CL-BART to a study of the impact of heat waves on people with Alzheimer's disease in California and effect modification by other chronic conditions. Through this application, we also describe strategies to examine heterogeneous odds ratios through variable importance, partial dependence, and lower-dimensional summaries. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
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