Literature DB >> 21882285

Accounting for between-study variation in incremental net benefit in value of information methodology.

Andrew R Willan1, Simon Eckermann.   

Abstract

Previous applications of value of information methods for determining optimal sample size in randomized clinical trials have assumed no between-study variation in mean incremental net benefit. By adopting a hierarchical model, we provide a solution for determining optimal sample size with this assumption relaxed. The solution is illustrated with two examples from the literature. Expected net gain increases with increasing between-study variation, reflecting the increased uncertainty in incremental net benefit and reduced extent to which data are borrowed from previous evidence. Hence, a trial can become optimal where current evidence is sufficient assuming no between-study variation. However, despite the expected net gain increasing, the optimal sample size in the illustrated examples is relatively insensitive to the amount of between-study variation. Further percentage losses in expected net gain were small even when choosing sample sizes that reflected widely different between-study variation.
Copyright © 2011 John Wiley & Sons, Ltd.

Mesh:

Year:  2011        PMID: 21882285     DOI: 10.1002/hec.1781

Source DB:  PubMed          Journal:  Health Econ        ISSN: 1057-9230            Impact factor:   3.046


  2 in total

Review 1.  Sample size determination for cost-effectiveness trials.

Authors:  Andrew R Willan
Journal:  Pharmacoeconomics       Date:  2011-11       Impact factor: 4.981

2.  Computing Expected Value of Partial Sample Information from Probabilistic Sensitivity Analysis Using Linear Regression Metamodeling.

Authors:  Hawre Jalal; Jeremy D Goldhaber-Fiebert; Karen M Kuntz
Journal:  Med Decis Making       Date:  2015-04-03       Impact factor: 2.583

  2 in total

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