Distribution of the two‐sample t‐test statistic following blinded sample size re‐estimation
Abstract
We consider the blinded sample size re‐estimation based on the simple one‐sample variance estimator at an interim analysis. We characterize the exact distribution of the standard two‐sample t‐test statistic at the final analysis. We describe a simulation algorithm for the evaluation of the probability of rejecting the null hypothesis at given treatment effect. We compare the blinded sample size re‐estimation method with two unblinded methods with respect to the empirical type I error, the empirical power, and the empirical distribution of the standard deviation estimator and final sample size. We characterize the type I error inflation across the range of standardized non‐inferiority margin for non‐inferiority trials, and derive the adjusted significance level to ensure type I error control for given sample size of the internal pilot study. We show that the adjusted significance level increases as the sample size of the internal pilot study increases. Copyright © 2016 John Wiley & Sons, Ltd.
Citing Literature
Number of times cited according to CrossRef: 3
- Olusegun K. Phillips-Alonge, The influence of partnering on the occurrence of construction requirement conflicts and disputes, International Journal of Construction Management, 10.1080/15623599.2018.1435236, (1-16), (2018).
- Tobias Mütze, Tim Friede, Blinded sample size re‐estimation in three‐arm trials with ‘gold standard’ design, Statistics in Medicine, 10.1002/sim.7356, 36, 23, (3636-3653), (2017).
- Martin Posch, Florian Klinglmueller, Franz König, Frank Miller, Estimation after blinded sample size reassessment, Statistical Methods in Medical Research, 10.1177/0962280216670424, (096228021667042), (2016).




