A Weighted Risk Set Estimator for Survival Distributions in Two-Stage Randomization Designs with Censored Survival Data

Guo Xiang and Tsiatis Anastasios
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Guo Xiang: North Carolina State University
Tsiatis Anastasios: North Carolina State University

The International Journal of Biostatistics, 2005, vol. 1, issue 1, 17

Abstract: In many clinical trials related to diseases such as cancers and HIV, patients are treated by different combinations of therapies. This leads to two-stage designs, where patients are initially randomized to a primary therapy and then depending on disease remission and patients' consent, a maintenance therapy will be randomly assigned. In such designs, the effects of different treatment policies, i.e., combinations of primary and maintenance therapy are of great interest. In this paper, we propose an estimator for the survival distribution for each treatment policy in such two-stage studies with right-censoring using the method of weighted estimation equations within risk sets. We also derive the large-sample properties. The method is demonstrated and compared with other estimators through simulations and applied to analyze a two-stage randomized study with leukemia patients.

Keywords: Counting process; Induction therapy; Inverse Weighting; Maintenance therapy; Risk sets; Potential outcomes; Survival analysis (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (3)

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DOI: 10.2202/1557-4679.1000

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