Blinded sample size recalculation for clinical trials with normal data and baseline adjusted analysis

Baseline adjusted analyses are commonly encountered in practice, and regulatory guidelines endorse this practice. Sample size calculations for this kind of analyses require knowledge of the magnitude of nuisance parameters that are usually not given when the results of clinical trials are reported i...

Full description

Saved in:
Bibliographic Details
Main Authors: Friede, Tim (Author) , Kieser, Meinhard (Author)
Format: Article (Journal)
Language:English
Published: 2011
In: Pharmaceutical statistics
Year: 2011, Volume: 10, Issue: 1, Pages: 8-13
ISSN:1539-1612
DOI:10.1002/pst.398
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1002/pst.398
Verlag, lizenzpflichtig, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/pst.398
Get full text
Author Notes:Tim Friede and Meinhard Kieser
Description
Summary:Baseline adjusted analyses are commonly encountered in practice, and regulatory guidelines endorse this practice. Sample size calculations for this kind of analyses require knowledge of the magnitude of nuisance parameters that are usually not given when the results of clinical trials are reported in the literature. It is therefore quite natural to start with a preliminary calculated sample size based on the sparse information available in the planning phase and to re-estimate the value of the nuisance parameters (and with it the sample size) when a portion of the planned number of patients have completed the study. We investigate the characteristics of this internal pilot study design when an analysis of covariance with normally distributed outcome and one random covariate is applied. For this purpose we first assess the accuracy of four approximate sample size formulae within the fixed sample size design. Then the performance of the recalculation procedure with respect to its actual Type I error rate and power characteristics is examined. The results of simulation studies show that this approach has favorable properties with respect to the Type I error rate and power. Together with its simplicity, these features should make it attractive for practical application. Copyright © 2009 John Wiley & Sons, Ltd.
Item Description:Gesehen am 24.04.2023
Online veröffentlicht am 26. November 2009
Physical Description:Online Resource
ISSN:1539-1612
DOI:10.1002/pst.398