Literature DB >> 23399102

A C++ program to calculate sample sizes for cost-effectiveness trials in a Bayesian framework.

Shah-Jalal Sarker1, Anne Whitehead, Iftekhar Khan.   

Abstract

Cost-Effectiveness Analysis (CEA) has become an increasingly important component of clinical trials. However, formal sample size calculations for such studies are not common. One of the reasons for this might be due to the absence of readily available computer software to perform complex calculations, particularly in a Bayesian setting. In this paper, a C++ program (using NAG library functions/subroutines) is presented to estimate the sample sizes for cost-effectiveness clinical trials in a Bayesian framework. The program can equally be used to calculate sample sizes for efficacy trials. The Bayesian approach to sample size calculation is based on that of O'Hagan and Stevens (A. O'Hagan, J.W. Stevens, Bayesian assessment of sample size for clinical trials of cost-effectiveness, Medical Decision Making 21 (2001) 219-230). With this program, the user can calculate sample sizes for various thresholds of willingness to pay and under various assumptions of the correlations between cost and effects. Under some prior, the program produces frequentist sample size as well. The program runs under windows environment and running time is very short.
Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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Year:  2013        PMID: 23399102     DOI: 10.1016/j.cmpb.2013.01.008

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  2 in total

1.  Bayesian sample size determination for cost-effectiveness studies with censored data.

Authors:  Daniel P Beavers; James D Stamey
Journal:  PLoS One       Date:  2018-01-05       Impact factor: 3.240

2.  Cost-Effectiveness and Cost-Utility Analysis of the Treatment of Emotional Disorders in Primary Care: PsicAP Clinical Trial. Description of the Sub-study Design.

Authors:  Paloma Ruiz-Rodríguez; Antonio Cano-Vindel; Roger Muñoz-Navarro; Cristina M Wood; Leonardo A Medrano; Luciana Sofía Moretti
Journal:  Front Psychol       Date:  2018-03-06
  2 in total

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