Detecting qualitative interactions in clinical trials with binary responses

2014 ◽  
Vol 13 (5) ◽  
pp. 309-315 ◽  
Author(s):  
Andreas Kitsche
Keyword(s):  
Clinical Trials ◽  
Binary Responses

Incorporating intermediate binary responses into interim analyses of clinical trials: A comparison of four methods

2008 ◽  
Vol 27 (10) ◽  
pp. 1646-1666 ◽  
Author(s):  
Anne Whitehead ◽  
Marina Roshini Sooriyarachchi ◽  
John Whitehead ◽  
Kim Bolland
Keyword(s):  
Clinical Trials ◽  
Binary Responses ◽  
Interim Analyses

Multiple-objective response-adaptive repeated measurement designs in clinical trials for binary responses

2013 ◽  
Vol 33 (4) ◽  
pp. 607-617 ◽  
Author(s):  
Yuanyuan Liang ◽  
Yin Li ◽  
Jing Wang ◽  
Keumhee C. Carriere
Keyword(s):  
Clinical Trials ◽  
Objective Response ◽  
Repeated Measurement ◽  
Multiple Objective ◽  
Binary Responses

scholarly journals A Test for Multiple Binary Endpoints with Continuous Latent Distribution in Clinical Trials

2021 ◽  
Vol 20 (4) ◽  
pp. 463-480
Author(s):  
Takuma Ishihara ◽  
Kouji Yamamoto
Keyword(s):  
Clinical Trials ◽  
Latent Variables ◽  
Testing Procedure ◽  
Association Measure ◽  
Binary Responses ◽  
Testing Procedures ◽  
Primary Endpoints ◽  
Latent Distribution ◽  
Multiple Primary ◽  
Continuous Responses

AbstractIn clinical trials, two or more binary responses obtained by dichotomizing continuous responses are often employed as multiple primary endpoints. Testing procedures for multiple binary variables with latent distribution have not yet been adequately discussed. Based on the association measure among latent variables, we provide a statistic for testing the superiority of at least one binary endpoint. In addition, we propose a testing procedure with a framework in which the trial efficacy is confirmed only when there is superiority of at least one endpoint and non-inferiority of the remaining endpoints. The performance of the proposed procedure is evaluated through simulations.

Bayesian optimal response-adaptive design for binary responses using stopping rule

2016 ◽  
Vol 27 (3) ◽  
pp. 891-904 ◽  
Author(s):  
Fumiyasu Komaki ◽  
Atanu Biswas
Keyword(s):  
Clinical Trials ◽  
Adaptive Design ◽  
Real Data ◽  
Adaptive Designs ◽  
Phase Iii ◽  
Data Set ◽  
Binary Responses ◽  
Phase Iii Clinical Trials ◽  
Number Of Patients ◽  
Response Adaptive Designs

Response-adaptive designs are used in phase III clinical trials to allocate a larger number of patients to the better treatment arm. Optimal designs are explored in the recent years in the context of response-adaptive designs, in the frequentist view point only. In the present paper, we propose some response-adaptive designs for two treatments based on Bayesian prediction for phase III clinical trials. Some properties are studied and numerically compared with some existing competitors. A real data set is used to illustrate the applicability of the proposed methodology where we redesign the experiment using parameters derived from the data set.

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