Literature DB >> 7569500

Bayesian predictive approach for inference about proportions.

B Lecoutre1, G Derzko, J M Grouin.   

Abstract

This paper investigates the Bayesian procedures for comparing proportions. These procedures are especially suitable for accepting (or rejecting) the equivalence of two population proportions. Furthermore the Bayesian predictive probabilities provide a natural and flexible tool in monitoring trials, especially for choosing a sample size and for conducting interim analyses. These methods are illustrated with two examples where antithrombotic treatments are administrated to prevent further occurrences of thromboses.

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Year:  1995        PMID: 7569500     DOI: 10.1002/sim.4780140924

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  5 in total

1.  Optimal and lead-in adaptive allocation for binary outcomes: a comparison of Bayesian methodologies.

Authors:  Roy T Sabo; Ghalib Bello
Journal:  Commun Stat Theory Methods       Date:  2016-04-08       Impact factor: 0.893

2.  Application of adaptive design methodology in development of a long-acting glucagon-like peptide-1 analog (dulaglutide): statistical design and simulations.

Authors:  Zachary Skrivanek; Scott Berry; Don Berry; Jenny Chien; Mary Jane Geiger; James H Anderson; Brenda Gaydos
Journal:  J Diabetes Sci Technol       Date:  2012-11-01

3.  Epigenetic induction of adaptive immune response in multiple myeloma: sequential azacitidine and lenalidomide generate cancer testis antigen-specific cellular immunity.

Authors:  Amir A Toor; Kyle K Payne; Harold M Chung; Roy T Sabo; Allison F Hazlett; Maciej Kmieciak; Kimberly Sanford; David C Williams; William B Clark; Catherine H Roberts; John M McCarty; Masoud H Manjili
Journal:  Br J Haematol       Date:  2012-07-23       Impact factor: 6.998

4.  A double-blind randomized phase II dose-finding study of olanzapine 10 mg or 5 mg for the prophylaxis of emesis induced by highly emetogenic cisplatin-based chemotherapy.

Authors:  Takako Yanai; Satoru Iwasa; Hironobu Hashimoto; Fumiyoshi Ohyanagi; Tomomi Takiguchi; Koji Takeda; Masahiko Nakao; Hiroshi Sakai; Toshiaki Nakayama; Koichi Minato; Takahiro Arai; Kenichi Suzuki; Yasuhiro Shimada; Kengo Nagashima; Hiroyuki Terakado; Noboru Yamamoto
Journal:  Int J Clin Oncol       Date:  2017-10-16       Impact factor: 3.402

5.  The utility of Bayesian predictive probabilities for interim monitoring of clinical trials.

Authors:  Benjamin R Saville; Jason T Connor; Gregory D Ayers; JoAnn Alvarez
Journal:  Clin Trials       Date:  2014-05-28       Impact factor: 2.486

  5 in total

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