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Permutation tests for comparing marginal survival functions with clustered failure time data
1Department of Biostatistics, University of North Carolina at Chapel Hill, 27599-7400, USA. cat@bios.unc.edu
Abstract:
We propose a class of two-sample non-parametric permutation tests to compare the marginal survival distributions of two groups when the failure times are correlated within cluster, with clusters nested within each group. The permutation distribution effectively takes into account the correlation between failure times within a cluster. The method is able to handle data with clusters of either fixed or variable sizes. Moreover, this class of test statistics is sensitive to various alternatives. The size and power of the proposed tests are assessed by a series of simulation studies. The method is illustrated by application to data from the Hypertension Detection and Follow-up program trial.