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).

Viewing alternatives

Metrics

Item Actions

Export

You can export this page using these formats Digital Object Identifier - DOI

About

• Item ORO ID
• 48017
• Item Type
• Journal Item
• ISSN
• 0167-9473
• Project Funding Details

• Funded Project Name	Project ID	Funding Body
  MethodologyGrant	MR/L009005/1	MRC (Medical Research Council)

• Keywords
• Self-controlled case series; Competing risks; Multiple events
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Copyright Holders
• © 2016 Elsevier B.V.
• Depositing User
• Yonas Ghebremichael-Weldeselassie