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.

[1]  P. Bauer,et al.  Evaluation of experiments with adaptive interim analyses. , 1994, Biometrics.

[2]  H. Schäfer,et al.  Adaptive Group Sequential Designs for Clinical Trials: Combining the Advantages of Adaptive and of Classical Group Sequential Approaches , 2001, Biometrics.

[3]  W. Lehmacher,et al.  Adaptive Sample Size Calculations in Group Sequential Trials , 1999, Biometrics.

[4]  M. Proschan,et al.  Designed extension of studies based on conditional power. , 1995 .

[5]  J. Wittes,et al.  The role of internal pilot studies in increasing the efficiency of clinical trials. , 1990, Statistics in medicine.

[6]  H. Schäfer,et al.  Modification of the sample size and the schedule of interim analyses in survival trials based on data inspections , 2001, Statistics in medicine.

[7]  W. Brannath,et al.  Recursive Combination Tests , 2002 .

[8]  C Jennison,et al.  Estimating the sample size for a t-test using an internal pilot. , 1999, Statistics in medicine.

[9]  T. Friede,et al.  Re-calculating the sample size in internal pilot study designs with control of the type I error rate. , 2000, Statistics in medicine.

[10]  Martin Posch,et al.  Conditional Rejection Probabilities of Student's t‐test and Design Adaptations , 2004 .

[11]  Anastasios A. Tsiatis,et al.  Flexible Sample Size Considerations Using Information-Based Interim Monitoring , 2001 .

[12]  H. Schäfer,et al.  A general statistical principle for changing a design any time during the course of a trial , 2004, Statistics in medicine.

[13]  C Jennison,et al.  A group sequential t-test with updating of sample size , 2000 .

[14]  S. Day,et al.  Internal pilot studies for estimating sample size. , 1994, Statistics in medicine.

[15]  J. Denne,et al.  Sample size recalculation using conditional power , 2001, Statistics in medicine.

[16]  Christopher Jennison,et al.  Exact calculations for sequential t, X2 and F tests , 1991 .

[17]  C. Stein.  A Two-Sample Test for a Linear Hypothesis Whose Power is Independent of the Variance , 1945 .