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Comparing k-independent and right censored samples based on the likelihood ratio

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Abstract

Powerful k-sample tests to compare the equality of the underlying distributions of right censored data based on the likelihood ratio are proposed. Their statistical power is studied and compared with that of commonly used tests by Monte Carlo simulations. A real data analysis is also considered. It is observed that the new likelihood ratio based tests are clearly more powerful than the traditional ones when there not exists uniform dominance among the involved distributions. Besides, the new tests turn out to be as powerful as the best classical test otherwise.

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Authors and Affiliations

  1. CIBER Epidemiología y SP, Subdirección de SP de Gipuzkoa, Donostia, Spain

    Pablo Martínez-Camblor

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  1. Pablo Martínez-Camblor
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Correspondence to Pablo Martínez-Camblor.

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Martínez-Camblor, P. Comparing k-independent and right censored samples based on the likelihood ratio. Comput Stat 25, 363–374 (2010). https://doi.org/10.1007/s00180-009-0181-9

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  • DOI: https://doi.org/10.1007/s00180-009-0181-9

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