Interval estimation for response adaptive clinical trials
David Tolusso and
Xikui Wang
Computational Statistics & Data Analysis, 2011, vol. 55, issue 1, 725-730
Abstract:
In this paper we examine a new method for constructing confidence intervals for the difference of success probabilities to analyze dependent data from response adaptive designs with binary responses. Specifically we investigate the feasibility of the Jeffreys-Perks procedure for interval estimation. Simulation results are derived to demonstrate the performance of the Jeffreys-Perks procedure compared with the profile likelihood method. It is found that both asymptotic methods perform well for small sample sizes despite being approximate procedures.
Keywords: Adaptive; allocation; Two-sample; binomial; Interval; estimation; Profile; likelihood; Randomized; play-the-winner; rule (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-9473(10)00261-6
Full text for ScienceDirect subscribers only.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:55:y:2011:i:1:p:725-730
Access Statistics for this article
Computational Statistics & Data Analysis is currently edited by S.P. Azen
More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().