The Annals of Statistics
- Ann. Statist.
- Volume 23, Number 1 (1995), 234-254.
Central Limit Theorems for Doubly Adaptive Biased Coin Designs
Asymptotic normality of the difference between the number of subjects assigned to a treatment and the desired number to be assigned is established for allocation rules which use Eisele's biased coin design. Subject responses are assumed to be independent random variables from standard exponential families. In the proof, it is shown that the difference may be magnified by appropriate constants so that the magnified difference is nearly a martingale. An application to the Behrens-Fisher problem in the normal case is described briefly.
Ann. Statist., Volume 23, Number 1 (1995), 234-254.
First available in Project Euclid: 11 April 2007
Permanent link to this document
Digital Object Identifier
Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
Eisele, Jeffrey R.; Woodroofe, Michael B. Central Limit Theorems for Doubly Adaptive Biased Coin Designs. Ann. Statist. 23 (1995), no. 1, 234--254. doi:10.1214/aos/1176324465. https://projecteuclid.org/euclid.aos/1176324465