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Sensitivity of the hazard ratio to nonignorable treatment assignment in an observational study
Author(s) -
Mitra Nandita,
Heitjan Daniel F.
Publication year - 2006
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.2606
Subject(s) - covariate , observational study , hazard ratio , propensity score matching , statistics , sensitivity (control systems) , econometrics , hazard , medicine , computer science , mathematics , confidence interval , chemistry , organic chemistry , electronic engineering , engineering
In non‐randomized studies, estimation of treatment effects generally requires adjustment for imbalances in observed covariates. One such method, based on the propensity score, is useful in many applications but may be biased when the assumption of strongly ignorable treatment assignment is violated. Because it is not possible to evaluate this assumption from the data, it is advisable to assess the sensitivity of conclusions to violations of strong ignorability. Lin et al . ( Biomet . 1998; 54 :948–963) have implemented this idea by investigating how an unmeasured covariate may affect the conclusions of an observational study. We extend their method to assess sensitivity of the treatment hazard ratio to hidden bias under a range of covariate distributions. We derive simple formulas for approximating the true from the apparent treatment hazard ratio estimated under a specific survival model, and assess the validity of these formulas in simulation studies. We demonstrate the method in an analysis of SEER‐Medicare data on the effects of chemotherapy in elderly colon cancer patients.Copyright © 2006 John Wiley & Sons, Ltd.