Self-controlled case series with multiple event types

Yonas Ghebremichael-Weldeselassie, Heather J. Whitaker, Ian J. Douglas, Liam Smeeth and C. Paddy Farrington

Computational Statistics & Data Analysis, 2017, vol. 113, issue C, 64-72

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).

Keywords: Self-controlled case series; Competing risks; Multiple events (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:113:y:2017:i:c:p:64-72

DOI: 10.1016/j.csda.2016.10.010

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