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Related Experiment Videos

Pulling cost-effectiveness analysis up by its bootstraps: a non-parametric approach to confidence interval estimation

A H Briggs1, D E Wonderling, C Z Mooney

  • 1Health Economics Research Centre, University of Oxford, UK.

Health Economics
|July 1, 1997
PubMed
Summary

Non-parametric bootstrap confidence intervals offer a way to estimate uncertainty in the incremental cost effectiveness ratio (ICER) without relying on specific data distribution assumptions. While promising, bootstrap estimates for bias and standard error require cautious interpretation due to potential instability.

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Area of Science:

  • Health economics
  • Biostatistics
  • Clinical trial analysis

Background:

  • The incremental cost effectiveness ratio (ICER) is a key statistic in health care economic evaluations.
  • Quantifying uncertainty in ICER estimates is crucial when patient-specific cost and outcome data are available.
  • Parametric methods have been the focus for constructing confidence intervals for ICERs.

Purpose of the Study:

  • To describe the construction and application of non-parametric bootstrap confidence intervals for ICERs.
  • To evaluate the strengths and weaknesses of the non-parametric bootstrap approach.
  • To assess the utility of bootstrap confidence intervals in estimating ICER uncertainty.

Main Methods:

  • Application of the non-parametric bootstrap method to clinical trial data.

Related Experiment Videos

  • Detailed description of bootstrap confidence interval construction.
  • Successive examination of bootstrap confidence limits with increasing replications.

    • Main Results:

    • Non-parametric bootstrap confidence intervals do not rely on parametric assumptions about the ICER's sampling distribution.
    • Percentile bootstrap confidence intervals show promise for estimating ICER uncertainty.
    • Successive bootstrap estimates of bias and standard error indicated potential instability.

    Conclusions:

    • Non-parametric bootstrap confidence intervals are a valuable tool for assessing ICER uncertainty.
    • Caution is advised when interpreting bootstrap-derived estimates of bias and standard error due to observed instability.
    • Further investigation into the stability of bootstrap estimates is recommended for robust economic evaluations.