Medical College of Wisconsin
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Asymptotic properties of maximum likelihood estimators with sample size recalculation. Stat Pap (Berl) 2019 Apr;60(2):373-394



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Consider an experiment in which the primary objective is to determine the significance of a treatment effect at a predetermined type I error and statistical power. Assume that the sample size required to maintain these type I error and power will be re-estimated at an interim analysis. A secondary objective is to estimate the treatment effect. Our main finding is that the asymptotic distributions of standardized statistics are random mixtures of distributions, which are non-normal except under certain model choices for sample size re-estimation (SSR). Monte-Carlo simulation studies and an illustrative example highlight the fact that asymptotic distributions of estimators with SSR may differ from the asymptotic distribution of the same estimators without SSR.

Author List

Tarima S, Flournoy N


Sergey S. Tarima PhD Associate Professor in the Institute for Health and Equity department at Medical College of Wisconsin

jenkins-FCD Prod-486 e3098984f26de787f5ecab75090d0a28e7f4f7c0