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Two-stage nonparametric bootstrap sampling with shrinkage correction for clustered data

Author

Listed:
  • Edmond S.-W. Ng

    (London School of Hygiene and Tropical Medicine)

  • Richard Grieve

    (London School of Hygiene and Tropical Medicine)

  • James R. Carpenter

    (London School of Hygiene and Tropical Medicine)

Abstract

This article describes a new Stata command, tsb, for performing a stratified two-stage nonparametric bootstrap resampling procedure for clustered data. Estimates for uncertainty around the point estimate, such as standard error and confidence intervals, are derived from the resultant bootstrap samples. A shrinkage estimator proposed for correcting possible overestimation due to secondstage sampling is implemented as default. Although this command is written with cost effectiveness analyses alongside cluster trials in mind, it is applicable to the analysis of continuous endpoints in cluster trials more generally. The use of this command is exemplified with a case study of a cost effectiveness analysis undertaken alongside a cluster randomized trial. We also report bootstrap confidence interval coverage by using data from a published simulation study. Copyright 2013 by StataCorp LP.

Suggested Citation

  • Edmond S.-W. Ng & Richard Grieve & James R. Carpenter, 2013. "Two-stage nonparametric bootstrap sampling with shrinkage correction for clustered data," Stata Journal, StataCorp LP, vol. 13(1), pages 141-164, March.
    • Handle: RePEc:tsj:stataj:v:13:y:2013:i:1:p:141-164
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    References listed on IDEAS

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    1. Richard M. Nixon & David Wonderling & Richard D. Grieve, 2010. "Non‐parametric methods for cost‐effectiveness analysis: the central limit theorem and the bootstrap compared," Health Economics, John Wiley & Sons, Ltd., vol. 19(3), pages 316-333, March.
    2. Andrew Briggs & Richard Nixon & Simon Dixon & Simon Thompson, 2005. "Parametric modelling of cost data: some simulation evidence," Health Economics, John Wiley & Sons, Ltd., vol. 14(4), pages 421-428, April.
    3. 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.
    4. Manning, Willard G., 1998. "The logged dependent variable, heteroscedasticity, and the retransformation problem," Journal of Health Economics, Elsevier, vol. 17(3), pages 283-295, June.
    5. Ben A. Van Hout & Maiwenn J. Al & Gilad S. Gordon & Frans F. H. Rutten, 1994. "Costs, effects and C/E‐ratios alongside a clinical trial," Health Economics, John Wiley & Sons, Ltd., vol. 3(5), pages 309-319, September.
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    1. Manju, Md Abu & Candel, Math J.J.M. & van Breukelen, Gerard J.P., 2021. "Robustness of cost-effectiveness analyses of cluster randomized trials assuming bivariate normality against skewed cost data," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    2. Mark Pennington & Jennifer Summers & Bola Coker & Saskia Eddy & Muralikrishnan R Kartha & Karen Edwards & Robert Freeman & John Goodden & Helen Powell & Christopher Verity & Janet L Peacock, 2020. "Selective dorsal rhizotomy; evidence on cost-effectiveness from England," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-13, August.

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