Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4949273 | Computational Statistics & Data Analysis | 2017 | 9 Pages |
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).
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Yonas Ghebremichael-Weldeselassie, Heather J. Whitaker, Ian J. Douglas, Liam Smeeth, C. Paddy Farrington,