Estimation of time-shift models with application to survival calibration in health technology assessment

Titman, Andrew Charles (2016) Estimation of time-shift models with application to survival calibration in health technology assessment. Statistics in Medicine, 35 (20). pp. 3645-3656. ISSN 0277-6715

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Abstract

The incremental life expectancy, defined as the difference in mean survival times between two treatment groups, is a crucial quantity of interest in cost-effectiveness analyses. Usually, this quantity is very difficult to estimate from censored survival data with a limited follow-up period. The paper develops estimation procedures for a time-shift survival model that, provided model assumptions are met, gives a reliable estimate of incremental life expectancy without extrapolation beyond the study period. Methods for inference are developed both for individual patient data and when only published Kaplan–Meier curves are available. Through simulation, the estimators are shown to be close to unbiased and constructed confidence intervals are shown to have close to nominal coverage for small to moderate sample sizes.

Item Type:
Journal Article
Journal or Publication Title:
Statistics in Medicine
Additional Information:
This is the peer reviewed version of the following article: Titman, A. C. (2016) Estimation of time-shift models with application to survival calibration in health technology assessment. Statist. Med., 35: 3645–3656. doi: 10.1002/sim.6951. which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/sim.6951/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
ID Code:
78896
Deposited By:
Deposited On:
01 Apr 2016 10:16
Refereed?:
Yes
Published?:
Published
Last Modified:
23 Sep 2020 02:43