Xavier de Luna
() and Per Johansson
Xavier de Luna: Department of Statistics, Umeå University, Postal: 901 87 Umeå, Sweden
Per Johansson: Institute for Labour Market Policy Evaluation, Postal: Box 513, 751 20 Uppsala, Sweden
Abstract: We perform inference on the effect of a treatment on survival times in studies where the treatment assignment is not randomized and the assignment time is not known in advance. We estimate survival functions on a treated and a control group which are made comparable through matching on observed covariates. The inference is performed by conditioning on waiting time to treatment, that is time between the entrance in the study and treatment. This can be done only when sufficient data is available. In other cases, averaging over waiting times is a possibility, although the classical interpretation of the estimated survival functions is lost unless hazards are not functions of the waiting times. To show unbiasedness and to obtain an estimator of the variance, we build on the potential outcome framework, which was introduced by J. Neyman in the context of randomized experiments, and adapted to observational studies by D. B. Rubin. Our approach does not make parametric or distributional assumptions. In particular, we do not assume proportionality of the hazards compared. Small sample performance of the estimator and a derived test of no treatment effect are studied in a Monte Carlo study.
37 pages, January 16, 2007
Full text files
Questions (including download problems) about the papers in this series should be directed to Monica Fällgren ()
Report other problems with accessing this service to Sune Karlsson ().
This page generated on 2018-01-23 23:33:31.