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Measuring Decision Sensitivity

Author

Listed:
  • Jon F. Merz
  • Mitchell J. Small
  • Paul S. Fischbeck

Abstract

Modeling of the uncertainty of multiple input variables for a complex decision problem com plicates sensitivity analysis. A method of analysis comprising stochastic simulation of the model and logistic regression of the simulated dichotomous decision variable against all of the input variables yields a direct measure of the importance of input variables to the decision. This method is demonstrated on a previously analyzed clinical decision either to continue observation or to immediately treat with anticoagulants a woman presenting with deep vein thrombosis in the first trimester of pregnancy. A relative measure of the importance of each input variable in causing a change of decision is estimated by calculating the change in the log odds attributable to variation of each input variable over its range of uncertain values compared with the total change of log odds from variation of all input variables. This method is compared with alternative measures of input variable importance, and is found to be a simple yet powerful tool for gaining quantitative insight into the nuances of a decision model. Key words: decision sensitivity; logistic regression; decision model; Monte Carlo technique. (Med Decis Making 1992;12:189-196)

Suggested Citation

  • Jon F. Merz & Mitchell J. Small & Paul S. Fischbeck, 1992. "Measuring Decision Sensitivity," Medical Decision Making, , vol. 12(3), pages 189-196, August.
    • Handle: RePEc:sae:medema:v:12:y:1992:i:3:p:189-196
    DOI: 10.1177/0272989X9201200304
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    References listed on IDEAS

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    1. Karen Klein & Stephen G. Pauker, 1981. "Recurrent Deep Venous Thrombosis in Pregnancy," Medical Decision Making, , vol. 1(2), pages 181-202, June.
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    Cited by:

    1. H. Christopher Frey & Sumeet R. Patil, 2002. "Identification and Review of Sensitivity Analysis Methods," Risk Analysis, John Wiley & Sons, vol. 22(3), pages 553-578, June.
    2. James C. Felli & Gordon B. Hazen, 1999. "A Bayesian approach to sensitivity analysis," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 263-268, May.

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