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

KRAUS, David. Adaptive Neyman's smooth tests of homogeneity of two samples of survival data. Journal of Statistical Planning and Inference. Amsterdam: Elsevier Science BV, 2009, roč. 139, č. 10, s. 3559-3569. ISSN 0378-3758. Dostupné z: https://dx.doi.org/10.1016/j.jspi.2009.04.009.

Základní údaje

• Originální název: Adaptive Neyman's smooth tests of homogeneity of two samples of survival data
• Autoři: KRAUS, David.
• Vydání: Journal of Statistical Planning and Inference, Amsterdam, Elsevier Science BV, 2009, 0378-3758.

Další údaje

• Originální jazyk: angličtina
• Typ výsledku: Článek v odborném periodiku
• Utajení: není předmětem státního či obchodního tajemství
• Impakt faktor: Impact factor: 0.725
• Doi: http://dx.doi.org/10.1016/j.jspi.2009.04.009
• UT WoS: 000268703700016
• Klíčová slova anglicky: Censoring; Neyman's smooth test; Schwarz's selection rule; Survival analysis; Two sample test
• Příznaky: Mezinárodní význam, Recenzováno

Anotace

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.