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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.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1016/j.csda.2016.10.010
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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 Item
Copyright Holders: 2016 Elsevier B.V.
ISSN: 0167-9473
Project Funding Details:
Funded Project NameProject IDFunding Body
MethodologyGrantMR/L009005/1MRC (Medical Research Council)
Keywords: Self-controlled case series; Competing risks; Multiple events
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 48017
Depositing User: Yonas Ghebremichael Weldeselassie
Date Deposited: 14 Dec 2016 16:42
Last Modified: 21 Sep 2019 08:50
URI: http://oro.open.ac.uk/id/eprint/48017
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