Bayesian analysis of time-series data under case-crossover designs: posterior equivalence and inference.

ABSTRACT: Case-crossover designs are widely used to study short-term exposure effects on the risk of acute adverse health events. While the frequentist literature on this topic is vast, there is no Bayesian work in this general area. The contribution of this paper is twofold. First, the paper establishes Bayesian equivalence results that require characterization of the set of priors under which the posterior distributions of the risk ratio parameters based on a case-crossover and time-series analysis are identical. Second, the paper studies inferential issues under case-crossover designs in a Bayesian framework. Traditionally, a conditional logistic regression is used for inference on risk-ratio parameters in case-crossover studies. We consider instead a more general full likelihood-based approach w

SUBMITTER: Li S 

PROVIDER: S-EPMC4108592 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature