Self-controlled case series with multiple event types

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: https://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).

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