Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/16128
Title: Stochastic EM algorithm for doubly interval-censored data
Authors: Dejardin, David
LESAFFRE, Emmanuel 
Issue Date: 2013
Source: BIOSTATISTICS, 14 (4), p. 766-778
Abstract: In clinical trials, it is frequently of interest to estimate the time between the onset of two events (e. g. duration of response in oncology). Here, we consider the case where subjects are assessed at fixed visits but the initial event and the terminating event occur in between visits. This type of data, called doubly interval censored, is often analyzed with standard survival techniques, assuming either that the survival time (between initial and terminating event) is known exactly or is single interval censored. We introduce a motivating dataset in which the interest is to evaluate the impact of the treatment on the duration of response endpoint. We review the existing approaches and discuss their limitations with respect to the characteristics of our motivating dataset. Furthermore, we propose a stochastic EM algorithm that overcomes the problems in the existing approaches. We show by simulations the finite sample properties of our approach.
Notes: Dejardin, D (reprint author), KULeuven, Interuniv Inst Biostat & Stat Bioinformat, Kapucijnenvoer 35,Blok D,Bus 7001, B-3000 Louvain, Belgium, david.dejardin@med.kuleuven.be
Keywords: Cox proportional hazard; Doubly interval censored; stochastic EM algorithm
Document URI: http://hdl.handle.net/1942/16128
ISSN: 1465-4644
e-ISSN: 1468-4357
DOI: 10.1093/biostatistics/kxt019
ISI #: 000328285800012
Rights: © The Author 2013. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Category: A1
Type: Journal Contribution
Validations: ecoom 2015
Appears in Collections:Research publications

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