Exact p-Values for Simon’s Two-Stage Designs in Clinical Trials

Guogen Shan, Hua Zhang, Tao Jiang (), Hanna Peterson, Daniel Young and Changxing Ma
Additional contact information
Guogen Shan: School of Community Health Sciences, University of Nevada Las Vegas
Hua Zhang: Zhejiang Gongshang University
Tao Jiang: Zhejiang Gongshang University
Hanna Peterson: School of Community Health Sciences, University of Nevada Las Vegas
Daniel Young: School of Community Health Sciences, University of Nevada Las Vegas
Changxing Ma: University at Buffalo

Statistics in Biosciences, 2016, vol. 8, issue 2, No 10, 357 pages

Abstract: Abstract In a one-sided hypothesis testing problem in clinical trials, the monotonic condition of a tail probability function is fundamentally important to guarantee that the actual type I and II error rates occur at the boundary of their associated parameter spaces. Otherwise, one has to search for the actual rates over the complete parameter space, which could be very computationally intensive. This important property has been extensively studied in traditional one-stage study settings (e.g., non-inferiority or superiority between two binomial proportions), but there is very limited research for this property in a two-stage design setting, e.g., Simon’s two-stage design. In this note, we theoretically prove that the tail probability is an increasing function of the parameter in Simon’s two-stage design. This proof not only provides theoretical justification that p-value occurs at the boundary of the parameter space, but also helps to reduce the computational intensity for study design search.

Keywords: Boundary; Mathematical induction; Monotonic condition; Simon’s two-stage design (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s12561-016-9152-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:stabio:v:8:y:2016:i:2:d:10.1007_s12561-016-9152-1

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/12561

DOI: 10.1007/s12561-016-9152-1

Access Statistics for this article

Statistics in Biosciences is currently edited by Hongyu Zhao and Xihong Lin

More articles in Statistics in Biosciences from Springer, International Chinese Statistical Association
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().