On adjustment for auxiliary covariates in additive hazard models for the analysis of randomized experiments

• 成果类型: Article
• 署名作者: Vansteelandt, S.; Martinussen, T.; Tchetgen, E. J.
• 署名单位: Ghent University; University of Copenhagen; Harvard University
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/ast045
• 发表日期: 2014
• 页码: 237244
• 关键词: incorrectly specified models; valid hypothesis tests; regression-models; clinical-trials; improving efficiency; collapsibility

摘要

We consider additive hazard models (Aalen, 1989) for the effect of a randomized treatment on a survival outcome, adjusting for auxiliary baseline covariates. We demonstrate that the Aalen least-squares estimator of the treatment effect parameter is asymptotically unbiased, even when the hazard's dependence on time or on the auxiliary covariates is misspecified, and even away from the null hypothesis of no treatment effect. We furthermore show that adjustment for auxiliary baseline covariates does not change the asymptotic variance of the estimator of the effect of a randomized treatment. We conclude that, in view of its robustness against model misspecification, Aalen least-squares estimation is attractive for evaluating treatment effects on a survival outcome in randomized experiments, and the primary reasons to consider baseline covariate adjustment in such settings could be interest in subgroup effects or the need to adjust for informative censoring or baseline imbalances. Our results also shed light on the robustness of Aalen least-squares estimators against model misspecification in observational studies.