Asymptotic properties of maximum likelihood estimators with sample size recalculation

Sergey Tarima () and Nancy Flournoy ()
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Sergey Tarima: Medical College of Wisconsin
Nancy Flournoy: University of Missouri

Statistical Papers, 2019, vol. 60, issue 2, No 3, 373-394

Abstract: Abstract 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.

Keywords: Adaptive designs; Asymptotic distribution theory; Interim analysis; Local alternatives; Maximum likelihood estimation; Mixture distributions; 62K99; 62L05; 62F05; 62E20 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s00362-019-01095-x

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