Premium
Estimation of time‐shift models with application to survival calibration in health technology assessment
Author(s) -
Titman Andrew C.
Publication year - 2016
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.6951
Subject(s) - life expectancy , extrapolation , estimator , statistics , inference , confidence interval , survival analysis , econometrics , estimation , calibration , sample size determination , computer science , mathematics , medicine , economics , population , artificial intelligence , environmental health , management
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. Copyright © 2016 John Wiley & Sons, Ltd.