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Saddlepoint $$p$$ p -values and confidence intervals for the class of linear rank tests for censored data under generalized randomized block design

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  • Ehab Abd-Elfattah

Abstract

One of the commonly used classes of tests for testing treatment effects for censored data is the linear rank class. The underlying distribution of this class is determined by the randomization design used to collect the data. Many randomization designs are used in clinical trials. The randomized block design is an important design that reduces selection bias and accidental bias. In this paper, a double saddlepoint approximation for the exact underlying randomization distribution for the linear rank class under generalized randomized block design is presented. Extensive simulation studies are used to assess the performance of the saddlepoint approximation. This approximation shows a great improvement in accuracy over the asymptotic normal approximation. This accuracy enables us to calculate almost exact confidence intervals for the treatment effect. Copyright Springer-Verlag Berlin Heidelberg 2015

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  • Ehab Abd-Elfattah, 2015. "Saddlepoint $$p$$ p -values and confidence intervals for the class of linear rank tests for censored data under generalized randomized block design," Computational Statistics, Springer, vol. 30(2), pages 593-604, June.
    • Handle: RePEc:spr:compst:v:30:y:2015:i:2:p:593-604
    DOI: 10.1007/s00180-014-0551-9
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    References listed on IDEAS

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    1. Ehab F. Abd-Elfattah & Ronald W. Butler, 2007. "The weighted log-rank class of permutation tests: P-values and confidence intervals using saddlepoint methods," Biometrika, Biometrika Trust, vol. 94(3), pages 543-551.
    2. A. C. Davison, 2002. "Saddlepoint approximations as smoothers," Biometrika, Biometrika Trust, vol. 89(4), pages 933-938, December.
    3. Yanqiong Zhang & William F. Rosenberger & Robert T. Smythe, 2007. "Sequential Monitoring of Randomization Tests: Stratified Randomization," Biometrics, The International Biometric Society, vol. 63(3), pages 865-872, September.
    4. Marco Marozzi, 2002. "Some notes on nonparametric inferences and permutation tests," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 139-151.
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