Bayesian designs and the control of frequentist characteristics: A practical solution-Reference-Cited by-同舟云学术

Bayesian designs and the control of frequentist characteristics: A practical solution

Published:2014-09-05 Issue:1 Volume:71 Page:218-226
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biom

Author:

Ventz Steffen¹,Trippa Lorenzo¹

Affiliation:

1. Department of Biostatistics and Computational Biology; Dana-Farber Cancer Institute and Department of Biostatistics Harvard School of Public Health; Boston Massachusetts 02115 U.S.A.

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/biom.12226/fullpdf

Reference36 articles.

1. Sequential medical trials;Anscombe;Journal of the American Statistical Association,1963

2. Repeated significance tests on accumulating data;Armitage;Journal of the Royal Statistical Society, Series A,1969

3. One-sided sequential stopping boundaries for clinical trials: A decision-theoretic approach;Berry;Biometrics,1988

4. Bayesian Adaptive Methods for Clinical Trials

5. Optimal Bayesian randomization;Berry;Journal of the Royal Statistical Society, Series B,1997

Cited by 31 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Are the tests overpowered or underpowered? A unified solution to correctly specify type I errors in design of clinical trials for two sample proportions;Statistics in Medicine;2024-02-19

2. Bayesian approach for design and analysis of medical device trials in the era of modern clinical studies;Medical Review;2023-10-01

3. A Bayesian multi‐arm multi‐stage clinical trial design incorporating information about treatment ordering;Statistics in Medicine;2023-05-09

4. Over-accrual in Bayesian adaptive trials with continuous futility stopping;Clinical Trials;2023-02-19

5. On Bayesian Sequential Clinical Trial Designs;The New England Journal of Statistics in Data Science;2023