Optimal Weighted Multiple-Testing Procedure for Clinical Trials

Hanan Hammouri, Marwan Alquran, Ruwa Abdel Muhsen and Jaser Altahat
Additional contact information
Hanan Hammouri: Department of Mathematics and Statistics, Jordan University of Science and Technology, Irbid 22110, Jordan
Marwan Alquran: Department of Mathematics and Statistics, Jordan University of Science and Technology, Irbid 22110, Jordan
Ruwa Abdel Muhsen: Department of Mathematics and Statistics, Jordan University of Science and Technology, Irbid 22110, Jordan
Jaser Altahat: Department of Mathematics and Statistics, Jordan University of Science and Technology, Irbid 22110, Jordan

Mathematics, 2022, vol. 10, issue 12, 1-19

Abstract: This paper describes a new method for testing randomized clinical trials with binary outcomes, which combines the O’Brien and Fleming (1979) multiple-testing procedure with optimal allocations and unequal weighted samples simultaneously. The O’Brien and Fleming method of group sequential testing is a simple and effective method with the same Type I error and power as a fixed one-stage chi-square test, with the option to terminate early if one treatment is clearly superior to another. This study modified the O’Brien and Fleming procedure, resulting in a more flexible new procedure, where the optimal allocation assists in allocating more subjects to the winning treatment without compromising the integrity of the study, while unequal weighting allows for different samples to be chosen for different stages of a trial. The new optimal weighted multiple-testing procedure (OWMP), based on simulation studies, is relatively robust to the added features because it showed a high preference for decreasing the Type I error and maintaining the power. In addition, the procedure was illustrated using simulated and real-life examples. The outcomes of the current study suggest that the new procedure is as effective as the original. However, it is more flexible.

Keywords: statistical algorithm; sequential group test; O’Brien and Fleming; Type I error and power; simulations; SAS software; hypotheses testing; biostatistics; categorical data analysis (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/12/1996/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/12/1996/ (text/html)

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:gam:jmathe:v:10:y:2022:i:12:p:1996-:d:835196

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().