An optimal design for screening trials
Wang, Y-G. & Leung, D. H. Y. (1998) An optimal design for screening trials. Biometrics, 54(1), pp. 243-250.
Yao, Begg, and Livingston (1996, Biometrics 52, 992-1001) considered the optimal group size for testing a series of potentially therapeutic agents to identify a promising one as soon as possible for given error rates. The number of patients to be tested with each agent was fixed as the group size. We consider a sequential design that allows early acceptance and rejection, and we provide an optimal strategy to minimize the sample sizes (patients) required using Markov decision processes. The minimization is under the constraints of the two types (false positive and false negative) of error probabilities, with the Lagrangian multipliers corresponding to the cost parameters for the two types of errors. Numerical studies indicate that there can be a substantial reduction in the number of patients required.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
|Item Type:||Journal Article|
|Additional Information:||ISI Document Delivery No.: ZF255
Times Cited: 10
Cited Reference Count: 6
Wang, YG Leung, DHY
International biometric soc
|Keywords:||dynamic programming, Markov decision process, optimality, sequential, clinical|
|Divisions:||Current > QUT Faculties and Divisions > Science & Engineering Faculty|
|Copyright Owner:||Biometrics © 1998|
|Deposited On:||18 Nov 2015 02:18|
|Last Modified:||18 Nov 2015 02:18|
Repository Staff Only: item control page