Blinded sample size re-estimation in superiority and noninferiority trials: bias versus variance in variance estimation
The internal pilot study design allows for modifying the sample size during an ongoing study based on a blinded estimate of the variance thus maintaining the trial integrity. Various blinded sample size re-estimation procedures have been proposed in the literature. We compare the blinded sample size...
Gespeichert in:
| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
19 March 2013
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| In: |
Pharmaceutical statistics
Year: 2013, Jahrgang: 12, Heft: 3, Pages: 141-146 |
| ISSN: | 1539-1612 |
| DOI: | https://doi.org/10.1002/pst.1564 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/https://doi.org/10.1002/pst.1564 Verlag, lizenzpflichtig, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/pst.1564 
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| Verfasserangaben: | Tim Friede and Meinhard Kieser |
MARC
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| 520 | |a The internal pilot study design allows for modifying the sample size during an ongoing study based on a blinded estimate of the variance thus maintaining the trial integrity. Various blinded sample size re-estimation procedures have been proposed in the literature. We compare the blinded sample size re-estimation procedures based on the one-sample variance of the pooled data with a blinded procedure using the randomization block information with respect to bias and variance of the variance estimators, and the distribution of the resulting sample sizes, power, and actual type I error rate. For reference, sample size re-estimation based on the unblinded variance is also included in the comparison. It is shown that using an unbiased variance estimator (such as the one using the randomization block information) for sample size re-estimation does not guarantee that the desired power is achieved. Moreover, in situations that are common in clinical trials, the variance estimator that employs the randomization block length shows a higher variability than the simple one-sample estimator and in turn the sample size resulting from the related re-estimation procedure. This higher variability can lead to a lower power as was demonstrated in the setting of noninferiority trials. In summary, the one-sample estimator obtained from the pooled data is extremely simple to apply, shows good performance, and is therefore recommended for application. Copyright © 2013 John Wiley & Sons, Ltd. | ||
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