Premium
A global logrank test for adaptive treatment strategies based on observational studies
Author(s) -
Li Zhiguo,
Valenstein Marcia,
Pfeiffer Paul,
Ganoczy Dara
Publication year - 2013
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.5987
Subject(s) - observational study , statistics , log rank test , test statistic , null hypothesis , statistic , sample size determination , statistical hypothesis testing , mathematics , econometrics , inverse probability , computer science , survival analysis , posterior probability , bayesian probability
In studying adaptive treatment strategies, a natural question that is of paramount interest is whether there is any significant difference among all possible treatment strategies. When the outcome variable of interest is time‐to‐event, we propose an inverse probability weighted logrank test for testing the equivalence of a fixed set of pre‐specified adaptive treatment strategies based on data from an observational study. The weights take into account both the possible selection bias in an observational study and the fact that the same subject may be consistent with more than one treatment strategy. The asymptotic distribution of the weighted logrank statistic under the null hypothesis is obtained. We show that, in an observational study where the treatment selection probabilities need to be estimated, the estimation of these probabilities does not have an effect on the asymptotic distribution of the weighted logrank statistic, as long as the estimation of the parameters in the models for these probabilities isn ‐consistent. Finite sample performance of the test is assessed via a simulation study. We also show in the simulation that the test can be pretty robust to misspecification of the models for the probabilities of treatment selection. The method is applied to analyze data on antidepressant adherence time from an observational database maintained at the Department of Veterans Affairs’ Serious Mental Illness Treatment Research and Evaluation Center. Copyright © 2013 John Wiley & Sons, Ltd.