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Problems with Interval Estimates of the Incremental Cost—Effectiveness Ratio

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  • Daniel F. Heitjan
  • Alan J. Moskowitz
  • William Whang

Abstract

The defining feature of a confidence interval is that it has a fixed minimum probability of covering the true value of the parameter being estimated, whatever the value of the parameter. The authors demonstrate by simulation that some recently proposed meth ods for interval estimation of the incremental cost—effectiveness ratio (ICER) either do not satisfy this definition or have other problems that limit their usefulness in applica tions. The problems are most prominent when the ICER is large and the true effec tiveness difference is small relative to its standard error. A modification of the percentile bootstrap confidence interval that involves a reordering of the sample space provides a partial solution of the problem. Key words: bootstrap; clinical trials; confidence inter vals ; cost—effectiveness ratios; Fieller's method; Taylor series. (Med Decis Making 1999;19:9-15)

Suggested Citation

  • Daniel F. Heitjan & Alan J. Moskowitz & William Whang, 1999. "Problems with Interval Estimates of the Incremental Cost—Effectiveness Ratio," Medical Decision Making, , vol. 19(1), pages 9-15, January.
    • Handle: RePEc:sae:medema:v:19:y:1999:i:1:p:9-15
    DOI: 10.1177/0272989X9901900102
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    References listed on IDEAS

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    1. Andrew H. Briggs & David E. Wonderling & Christopher Z. Mooney, 1997. "Pulling cost‐effectiveness analysis up by its bootstraps: A non‐parametric approach to confidence interval estimation," Health Economics, John Wiley & Sons, Ltd., vol. 6(4), pages 327-340, July.
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    Cited by:

    1. Daniel F. Heitjan, 2000. "Fieller's method and net health benefits," Health Economics, John Wiley & Sons, Ltd., vol. 9(4), pages 327-335, June.
    2. Anthony O’Hagan & John Stevens & Jacques Montmartin, 2000. "Inference for the Cost-Effectiveness Acceptability Curve and Cost-Effectiveness Ratio," PharmacoEconomics, Springer, vol. 17(4), pages 339-349, April.
    3. Jakob Bjørner & Hans Keiding, 2004. "Cost‐effectiveness with multiple outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 13(12), pages 1181-1190, December.
    4. Daniel F. Heitjan & Huiling Li, 2004. "Bayesian estimation of cost‐effectiveness: an importance‐sampling approach," Health Economics, John Wiley & Sons, Ltd., vol. 13(2), pages 191-198, February.
    5. Daniel F. Heitjan & Alan J. Moskowitz & William Whang, 1999. "Bayesian estimation of cost‐effectiveness ratios from clinical trials," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 191-201, May.

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