Publication details

Adaptive Neyman's smooth tests of homogeneity of two samples of survival data

Authors

KRAUS David

Year of publication 2009
Type Article in Periodical
Magazine / Source Journal of Statistical Planning and Inference
Citation
Doi http://dx.doi.org/10.1016/j.jspi.2009.04.009
Keywords Censoring; Neyman's smooth test; Schwarz's selection rule; Survival analysis; Two sample test
Description The problem of testing whether two samples of possibly right-censored survival data come from the same distribution is considered. The aim is to develop a test which is capable of detection of a wide spectrum of alternatives. A new class of tests based on Neyman's embedding idea is proposed. The null hypothesis is tested against a model where the hazard ratio of the two survival distributions is expressed by several smooth functions. A data-driven approach to the selection of these functions is studied. Asymptotic properties of the proposed procedures are investigated under fixed and local alternatives. Small-sample performance is explored via simulations which show that the power of the proposed tests appears to be more robust than the power of some versatile tests previously proposed in the literature (such as combinations of weighted logrank tests, or Kolmogorov-Smirnov tests). (C) 2009 Elsevier B.V. All rights reserved.

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