Farrington, Paddy; Anaya Izquierdo, Karim; Whitaker, Heather; Hocine, Mounia; Douglas, Ian and Smeeth, Liam
Due to copyright restrictions, this file is not available for public download
Click here to request a copy from the OU Author.
|DOI (Digital Object Identifier) Link:||http://doi.org/10.1198/jasa.2011.ap10108|
|Google Scholar:||Look up in Google Scholar|
The self-controlled case series method may be used to study the association between a time-varying exposure and a health event. It is based only on cases, and it controls for fixed confounders. Exposure and event histories are collected for each case over a predefined observation period. The method requires that observation periods should be independent of event times. This requirement is violated when events increase the mortality rate, since censoring of the observation periods is then event dependent. In this article, the case series method for rare nonrecurrent events is extended to remove this independence assumption, thus introducing an additional term in the likelihood that depends on the censoring process. In order to remain within the case series framework in which only cases are sampled, the model is reparameterized so that this additional term becomes estimable from the distribution of intervals from event to end of observation. The exposure effect of primary interest may be estimated unbiasedly. The age effect, however, takes on a new interpretation, incorporating the effect of censoring. The model may be fitted in standard loglinear modeling software; this yields conservative standard errors. We describe a detailed application to the study of antipsychotics and stroke. The estimates obtained from the standard case series model are shown to be biased when event-dependent observation periods are ignored. When they are allowed for, antipsychotic use remains strongly positively associated with stroke in patients with dementia, but not in patients without dementia. Two detailed simulation studies are included as Supplemental Material.
|Item Type:||Journal Article|
|Copyright Holders:||2011 American Statistical Association|
|Keywords:||censoring; conditional Poisson regression; epidemiologic study|
|Academic Unit/Department:||Mathematics, Computing and Technology > Mathematics and Statistics
Mathematics, Computing and Technology
|Depositing User:||Karim Anaya Izquierdo|
|Date Deposited:||18 May 2011 12:26|
|Last Modified:||25 Feb 2016 10:43|
|Share this page:|