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Biostatistics Advance Access originally published online on May 21, 2008
Biostatistics 2009 10(1):3-16; doi:10.1093/biostatistics/kxn013
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© The Author 2008. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

Case series analysis for censored, perturbed, or curtailed post-event exposures

C. Paddy Farrington*, Heather J. Whitaker and Mounia N. Hocine

Department of Mathematics and Statistics, The Open University, Milton Keynes MK7 6AA, UK c.p.farrington{at}open.ac.uk

* To whom correspondence should be addressed.

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.

Keywords: Censored data; Counterfactual; Endogeneity; Estimating equation; Horvitz–Thompson estimator; Pseudo-likelihood; Self-controlled case series

Received May 14, 2007; revised March 18, 2008; accepted for publication April 22, 2008.


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