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Self-controlled case series with multiple event types
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Ghebremichael-Weldeselassie, Yonas, Whitaker, Heather J., Douglas, Ian J., Smeeth, Liam and Farrington, C. Paddy (2017) Self-controlled case series with multiple event types. Computational Statistics & Data Analysis, 113 . pp. 64-72. doi:10.1016/j.csda.2016.10.010 ISSN 0167-9473.
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Official URL: http://dx.doi.org/10.1016/j.csda.2016.10.010
Abstract
Self-controlled case series methods for events that may be classified as one of several types are described. When the event is non-recurrent, the different types correspond to competing risks. It is shown that, under circumstances that are likely to arise in practical applications, the SCCS multi-type likelihood reduces to the product of the type-specific likelihoods. For recurrent events, this applies whether or not the marginal type-specific counts are dependent. As for the standard SCCS method, a rare disease assumption is required for non-recurrent events. Several forms of this assumption are investigated by simulation. The methods are applied to data on MMR vaccine and convulsions (febrile and non-febrile), and to data on thiazolidinediones and fractures (at different sites).
Item Type: | Journal Article | ||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences > Population, Evidence & Technologies (PET) Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School |
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Journal or Publication Title: | Computational Statistics & Data Analysis | ||||||||
Publisher: | Elsevier Science Ltd | ||||||||
ISSN: | 0167-9473 | ||||||||
Official Date: | September 2017 | ||||||||
Dates: |
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Volume: | 113 | ||||||||
Page Range: | pp. 64-72 | ||||||||
DOI: | 10.1016/j.csda.2016.10.010 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access |
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