Journal
BIOSTATISTICS
Volume 10, Issue 1, Pages 3-16Publisher
OXFORD UNIV PRESS
DOI: 10.1093/biostatistics/kxn013
Keywords
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Funding
- Engineering and Physical Sciences Research Council [EP/E02873X/1] Funding Source: researchfish
- EPSRC [EP/E02873X/1] Funding Source: UKRI
- Wellcome Trust [GR070346] Funding Source: Medline
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A new method is developed for analyzing case series data in situations where occurrence of the event censors, curtails, or otherwise affects post-event exposures. Unbiased estimating equations derived from the self-controlled case series model are adapted to allow for exposures whose occurrence or observation is influenced by the event. The method applies to transient point exposures and rare nonrecurrent events. Asymptotic efficiency is studied in some special cases. A computational scheme based on a pseudo-likelihood is proposed to make the computations feasible in complex models. Simulations, a validation study, and 2 applications are described.
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