Corrected profile likelihood confidence interval for binomial paired incomplete data. (7th January 2013)

• Record Type: Journal Article
• Authors: Pradhan, Vivek; Menon, Sandeep; Das, Ujjwal
• Is Part Of: Pharmaceutical statistics. Volume 12:Number 1(2013:Jan./Feb.)
• Page Start: 48
• Page End: 58
• Publication Date: 2013-01-07
• Subjects: Pharmacy -- Statistical methods -- Periodicals; Pharmacy -- Statistics -- Periodicals; 615.10727
• DOI: 10.1002/pst.1551
• Languages: English
• ISSNs: 1539-1604

Abstract

<abstract abstract-type="main" id="pst1551-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p id="pst1551-para-0001">Clinical trials often use paired binomial data as their clinical endpoint. The confidence interval is frequently used to estimate the treatment performance. Tang <italic>et al.</italic> (2009) have proposed exact and approximate unconditional methods for constructing a confidence interval in the presence of incomplete paired binary data. The approach proposed by Tang <italic>et al.</italic> can be overly conservative with large expected confidence interval width (ECIW) in some situations. We propose a profile likelihood‐based method with a Jeffreys' prior correction to construct the confidence interval. This approach generates confidence interval with a much better coverage probability and shorter ECIWs. The performances of the method along with the corrections are demonstrated through extensive simulation. Finally, three real world data sets are analyzed by all the methods. Statistical Analysis System (SAS) codes to execute the profile likelihood‐based methods are also presented. Copyright © 2013 John Wiley &amp; Sons, Ltd.</p> </abstract>