Increasing the sample size during clinical trials with t-distributed test statistics without inflating the type I error rate.
In clinical trials with t-distributed test statistics the required sample size depends on the unknown variance. Taking estimates from previous studies often leads to a misspecification of the true value of the variance. Hence, re-estimation of the variance based on the collected data and re-calculation of the required sample size is attractive. We present a flexible method for extensions of fixed sample or group-sequential trials with t-distributed test statistics. The method can be applied at any time during the course of the trial and does not require the necessity to pre-specify a sample size re-calculation rule. All available information can be used to determine the new sample size. The advantage of our method when compared with other adaptive methods is maintenance of the efficient t-test design when no extensions are actually made. We show that the type I error rate is preserved.
Timmesfeld
Nina
N
Institute of Medical Biometry and Epidemiology, Philipps University of Marburg, Bunsenstr. 3, Marburg D-35037, Germany. timmesfe@med.uni-marburg.de
Schäfer
Helmut
H
Müller
Hans-Helge
HH
D003198:Computer Simulation; D046690:Deep Brain Stimulation; D006801:Humans; D015233:Models, Statistical; D010300:Parkinson Disease / Q000628:therapy; D011788:Quality of Life; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D018401:Sample Size