Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Click here for more information

Sign In to gain access to subscriptions and/or personal tools.
Medical Decision Making
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Baker, S. G.
Right arrow Articles by Heidenberger, K.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Baker, S. G.
Right arrow Articles by Heidenberger, K.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Choosing Sample Sizes to Maximize Expected Health Benefits Subject to a Constraint on Total Trial Costs

Stuart G. Baker

Kurt Heidenberger

The authors present a method for choosing sample sizes for randomized controlled trials that maximizes expected health benefits (measured in expected discounted life years gained) subject to the decision maker's budget constraint. In comparison with similar approaches, the method introduces richer and more realistic models for the following quantities: costs and benefits during and after the trial, rates of adopting interventions after a positive rec ommendation, the distribution of data collected in the trial, and the decision to make a positive recommendation based on the results of the trial. Although the methodology is applicable to any type of trial, the emphasis in the paper is on prevention trials. Calculations involve Monte Carlo methods. An example is provided.

Key Words: Key words: Bayesian methods • resource allocation • decision analysis • stopping rules. (Med Decis Making 1989;9:14-25)

Medical Decision Making, Vol. 9, No. 1, 14-25 (1989)
DOI: 10.1177/0272989X8900900104


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?


This article has been cited by other articles:


Home page
JNCI J Natl Cancer InstHome page
S. G. Baker
Improving the Biomarker Pipeline to Develop and Evaluate Cancer Screening Tests
J Natl Cancer Inst, July 2, 2009; (2009) djp186v1.
[Abstract] [Full Text] [PDF]


Home page
Med Decis MakingHome page
L. Kessler and P. Taylor
Prevention Trials
Med Decis Making, February 1, 1989; 9(1): 1 - 2.
[PDF]