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Adjusting for bias in C/E ratio estimates

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  • Aaron A. Stinnett

Abstract

The estimator used to calculate incremental cost‐effectiveness (C/E) ratios from sampled data is biased but consistent. While the bias may be negligible in studies with large sample sizes, it is potentially important in analyses based on small samples. When patient‐level data on costs and effects are available, bootstrap simulation methods can be used to estimate the bias of a C/E ratio and adjust the point estimate accordingly.

Suggested Citation

  • Aaron A. Stinnett, 1996. "Adjusting for bias in C/E ratio estimates," Health Economics, John Wiley & Sons, Ltd., vol. 5(5), pages 470-472, September.
    • Handle: RePEc:wly:hlthec:v:5:y:1996:i:5:p:470-472
    DOI: 10.1002/(SICI)1099-1050(199609)5:53.0.CO;2-5
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    References listed on IDEAS

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    1. Dale J. Poirier, 1995. "Intermediate Statistics and Econometrics: A Comparative Approach," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262161494, April.
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    Cited by:

    1. Andrew Briggs & Paul Fenn, 1998. "Confidence intervals or surfaces? Uncertainty on the cost‐effectiveness plane," Health Economics, John Wiley & Sons, Ltd., vol. 7(8), pages 723-740, December.

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