Statistical inference for self-designing clinical trials with a one-sided hypothesis

Biometrics
Yu Shen, L Fisher

Abstract

In the process of monitoring clinical trials, it seems appealing to use the interim findings to determine whether the sample size originally planned will provide adequate power when the alternative hypothesis is true, and to adjust the sample size if necessary. In the present paper, we propose a flexible sequential monitoring method following the work of Fisher (1998), in which the maximum sample size does not have to be specified in advance. The final test statistic is constructed based on a weighted average of the sequentially collected data, where the weight function at each stage is determined by the observed data prior to that stage. Such a weight function is used to maintain the integrity of the variance of the final test statistic so that the overall type I error rate is preserved. Moreover, the weight function plays an implicit role in termination of a trial when a treatment difference exists. Finally, the design allows the trial to be stopped early when the efficacy result is sufficiently negative. Simulation studies confirm the performance of the method.

References

Aug 12, 1998·Statistics in Medicine·L D Fisher

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Citations

Jan 10, 2002·Statistics in Medicine·T Friede, M Kieser
Sep 22, 2007·Journal of Biopharmaceutical Statistics·Mark ChangKatherine McCarthy
Nov 21, 2007·Journal of Biopharmaceutical Statistics·Lin Wang, Lu Cui
Nov 9, 2010·Journal of Biopharmaceutical Statistics·Qing Liu, George Y H Chi
Dec 29, 2000·Biometrics·M Posch, P Bauer
Mar 17, 2001·Biometrics·Q Liu, G Y Chi
Jun 20, 2002·Biometrics·Chau T Thach, Lloyd D Fisher
Mar 20, 2009·Annual Review of Public Health·C Hendricks BrownRobert D Gibbons
Apr 18, 2001·Controlled Clinical Trials·J Hartung
Jan 1, 2013·Journal of Statistical Planning and Inference·Yi Cheng, Yu Shen
Jan 10, 2009·Contemporary Clinical Trials·Antje Jahn-Eimermacher, Katharina Ingel
Sep 26, 2015·Pharmaceutical Statistics·Andrew Montgomery Hartley
Mar 11, 2003·Statistics in Medicine·Martin PoschWerner Brannath
Mar 11, 2003·Statistics in Medicine·Christopher Jennison, Bruce W Turnbull
Apr 2, 2004·Statistics in Medicine·Y H Joshua ChenK K Gordon Lan
Feb 20, 2009·Statistics in Medicine·Heiko GötteAndreas Faldum
Mar 7, 2009·Statistics in Medicine·Werner BrannathAmy Racine-Poon
Sep 2, 2008·Biometrics·Werner BrannathMartin Posch
Apr 10, 2009·Biometrical Journal. Biometrische Zeitschrift·Michael A Proschan
Sep 16, 2006·Biometrical Journal. Biometrische Zeitschrift·Helmut SchäferHans-Helge Müller
Aug 11, 2006·Statistics in Medicine·Antje Jahn-Eimermacher, Gerhard Hommel
Sep 16, 2006·Biometrical Journal. Biometrische Zeitschrift·H M James HungJohn Lawrence
Sep 16, 2006·Biometrical Journal. Biometrische Zeitschrift·Gernot Wassmer
Oct 13, 2005·Statistics in Medicine·Werner BrannathPeter Bauer
Oct 13, 2005·Statistics in Medicine·Christopher Jennison, Bruce W Turnbull
Mar 22, 2016·Statistics in Medicine·Lanju ZhangBo Yang
Jan 8, 2014·Biometrical Journal. Biometrische Zeitschrift·Rene SchmidtJoachim Gerss
Mar 10, 2010·Statistics in Medicine·Carl-Fredrik Burman, Vera Lisovskaja
Jun 7, 2014·Journal of Biopharmaceutical Statistics·Meinhard Kieser, Stefan Englert
Apr 15, 2004·Drug Discovery Today·Peter Bauer, Werner Brannath
Oct 6, 2007·Statistics in Medicine·Cyrus R MehtaWerner Brannath
Feb 16, 2008·Statistics in Medicine·Jay Bartroff, Tze Leung Lai
Jul 19, 2005·Journal of Biopharmaceutical Statistics·H M James HungJohn Lawrence
Jun 2, 2012·Journal of Biopharmaceutical Statistics·Sandeep Menon, Mark Chang
Nov 4, 2006·Pharmaceutical Statistics·H M James HungRobert T O'Neill
Jan 19, 2012·Journal of Biopharmaceutical Statistics·Christina WunderLutz Edler
Jul 19, 2005·Journal of Biopharmaceutical Statistics·Christopher Jennison, Bruce W Turnbull
Jul 19, 2005·Journal of Biopharmaceutical Statistics·K K Gordon LanMey Wang
Sep 16, 2006·Biometrical Journal. Biometrische Zeitschrift·Joachim Hartung, Guido Knapp

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