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Flexible modelling of simultaneously interval censored and truncated time‐to‐event data
Author(s) -
Chebon Sammy,
Faes Christel,
Smedt Ann De,
Geys Helena
Publication year - 2015
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.1687
Subject(s) - overdispersion , cluster analysis , event (particle physics) , computer science , event data , statistics , interval (graph theory) , data mining , econometrics , mathematics , count data , poisson distribution , physics , quantum mechanics , combinatorics , analytics
This paper deals with the analysis of data from a HET‐CAM V T 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 & Sons, Ltd.