Unobserved covariates in the two-sample comparison of survival times: a maximin efficiency robust test
✍ Scribed by Philippe Broët; Thierry Moreau; Joseph Lellouch; Bernard Asselain
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 87 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0277-6715
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✦ Synopsis
In analysing a clinical trial with the logrank test, the hazards between the two groups are usually assumed to be proportional. Nevertheless, this hypothesis is no longer valid with unobserved covariates. As a consequence, there is a loss of power of the logrank test for testing the null hypothesis H0 of no treatment e ect. We propose a test suited for taking into account unobserved covariates. The proposed approach is based on a proportional hazard frailty model whereby the omitted covariates are considered as an unobserved frailty variable. The procedure is as follows. In a ÿrst step, the weighted logrank test optimal for testing H0 against a general proportional hazard frailty model is obtained and its specialization for a gamma frailty variable is derived. In a second step, the proposed test is obtained by combining the maximin e ciency robustness principle and the gamma frailty distribution properties. Simulation studies investigate the power properties of the test for di erent frailty distributions. A breast cancer clinical trial is analysed as an example. The proposed test might be recommended rather than the logrank for practical situations in which one expects heterogeneity related to omitted covariates.