This Article Full Text (OnlineFirst PDF) All Versions of this Article: 0272989X07311752v1 28/2/182    most recent Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Duintjer Tebbens, R. J. Articles by Cooke, R. M. Search for Related Content PubMed PubMed Citation Articles by Duintjer Tebbens, R. J. Articles by Cooke, R. M. Social Bookmarking                         What's this?

Uncertainty and Sensitivity Analyses of a Dynamic Economic Evaluation Model for Vaccination Programs

^* To whom correspondence should be addressed. E-mail: rduintje{at}hsph.harvard.edu.

	Abstract

With public health policy increasingly relying on mathematical models to provide insights about the impacts of potential policy options, the demand for uncertainty and sensitivity analyses that explore the implications of dif"ferent assumptions in a model continues to expand. Although analysts continue to develop methods to meet the demand, most modelers rely on a single method in the context of their assessments and presentations of results, and few analysts provide results that facilitate comparisons between uncertainty and sensitivity analysis methods. Methods vary in their degree of analytical difficulty and in the nature of the information that they provide, and analysts should communicate results with a note that not all methods yield the same insights. The authors explore several sensitivity analysis methods to test whether the choice of method affects the insights and importance rankings of inputs from the analysis. They use a dynamic cost-effectiveness model of a hypothetical infectious disease as the basis to perform 1-way and multiway sensitivity analyses, design of experiments, and Morris' method. They also compute partial derivatives as well as a number of probabilistic sensitivity measures, including correlations, regression coefficients, and the correlation ratio, to demonstrate the existing methods and to compare them. The authors find that the magnitudes and rankings of sensitivity measures depend on the selected method(s) and make recommendations regarding the choice of method depending on the complexity of the model, number of uncertain inputs, and desired types of insights from the sensitivity analysis. Key words: sensitivity analysis; uncertainty analysis; cost-effectiveness analysis; economic evaluation; decision analysis; design of experiments; dynamic infection transmission model. (Med Decis Making XXXX;XX:xx–xx)

First published on March 18, 2008, doi:10.1177/0272989X07311752

Medical Decision Making 2008;28:182.

A more recent version of this article appeared on March 1, 2008


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?