Flexible modelling of simultaneously interval censored and truncated time‐to‐event data. (7th May 2015)

• Record Type: Journal Article
• Authors: Chebon, Sammy; Faes, Christel; Smedt, Ann De; Geys, Helena
• Is Part Of: Pharmaceutical statistics. Volume 14:Number 4(2015:Jul./Aug.)
• Page Start: 311
• Page End: 321
• Publication Date: 2015-05-07
• Subjects: Pharmacy -- Statistical methods -- Periodicals; Pharmacy -- Statistics -- Periodicals; 615.10727
• DOI: 10.1002/pst.1687
• Languages: English
• ISSNs: 1539-1604

Abstract

<abstract abstract-type="main" id="pst1687-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p id="pst1687-para-0001">This paper deals with the analysis of data from a HET‐CAM^{<italic>V</italic><italic>T</italic>} experiment. From a statistical perspective, such data yield many challenges. First of all, the data are typically time‐to‐event like data, which are at the same time interval censored and right truncated. In addition, one has to cope with overdispersion as well as clustering. Traditional analysis approaches ignore overdispersion and clustering and summarize the data into a continuous score that can be analysed using simple linear models. In this paper, a novel combined frailty model is developed that simultaneously captures all of the aforementioned statistical challenges posed by the data. Copyright © 2015 John Wiley &amp; Sons, Ltd.</p> </abstract>