IDEAS home Printed from https://ideas.repec.org/a/tsj/stataj/v13y2013i1p141-164.html
   My bibliography  Save this article

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
    Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj13-1/st0288/
    as

    Download full text from publisher

    File URL: http://www.stata-journal.com/article.html?article=st0288
    File Function: link to article purchase
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    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. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jones, A.M, 2010. "Models For Health Care," Health, Econometrics and Data Group (HEDG) Working Papers 10/01, HEDG, c/o Department of Economics, University of York.
    2. 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.
    3. Andrew Briggs, 2012. "Statistical Methods for Cost-effectiveness Analysis Alongside Clinical Trials," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 50, Edward Elgar Publishing.
    4. Kobelt, G., 2013. "Health Economics: An Introduction to Economic Evaluation," Monographs, Office of Health Economics, number 000004.
    5. Borislava Mihaylova & Andrew Briggs & Anthony O'Hagan & Simon G. Thompson, 2011. "Review of statistical methods for analysing healthcare resources and costs," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 897-916, August.
    6. Bas Groot Koerkamp & Milton C. Weinstein & Theo Stijnen & M.H. Heijenbrok-Kal & M.G. Myriam Hunink, 2010. "Uncertainty and Patient Heterogeneity in Medical Decision Models," Medical Decision Making, , vol. 30(2), pages 194-205, March.
    7. David Meads & Andrea Marshall & Claire Hulme & Janet Dunn & Hugo Ford, 2016. "The Cost Effectiveness of Docetaxel and Active Symptom Control versus Active Symptom Control Alone for Refractory Oesophagogastric Adenocarcinoma: Economic Analysis of the COUGAR-02 Trial," PharmacoEconomics, Springer, vol. 34(1), pages 33-42, January.
    8. Andrew Willan, 2011. "Sample Size Determination for Cost-Effectiveness Trials," PharmacoEconomics, Springer, vol. 29(11), pages 933-949, November.
    9. Iris Arends & Ute Bültmann & Willem van Rhenen & Henk Groen & Jac J L van der Klink, 2013. "Economic Evaluation of a Problem Solving Intervention to Prevent Recurrent Sickness Absence in Workers with Common Mental Disorders," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-1, August.
    10. Patrick Richard & Regine Walker & Pierre Alexandre, 2018. "The burden of out of pocket costs and medical debt faced by households with chronic health conditions in the United States," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-13, June.
    11. Trottmann, Maria & Zweifel, Peter & Beck, Konstantin, 2012. "Supply-side and demand-side cost sharing in deregulated social health insurance: Which is more effective?," Journal of Health Economics, Elsevier, vol. 31(1), pages 231-242.
    12. Buntin, Melinda Beeuwkes & Zaslavsky, Alan M., 2004. "Too much ado about two-part models and transformation?: Comparing methods of modeling Medicare expenditures," Journal of Health Economics, Elsevier, vol. 23(3), pages 525-542, May.
    13. 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.
    14. Michael A. Clemens & Claudio Montenegro & Lant Pritchett, 2016. "Bounding the Price Equivalent of Migration Barriers," CID Working Papers 316, Center for International Development at Harvard University.
    15. Edward C. F. Wilson & Miranda Mugford & Garry Barton & Lee Shepstone, 2016. "Efficient Research Design," Medical Decision Making, , vol. 36(3), pages 335-348, April.
    16. Monica Merito & Patrizio Pezzotti, 2006. "Comparing costs and effectiveness of different starting points for highly active antiretroviral therapy in HIV-positive patients," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 7(1), pages 30-36, March.
    17. Kosteas, Vasilios D. & Renna, Francesco, 2014. "Plan choice, health insurance cost and premium sharing," Journal of Health Economics, Elsevier, vol. 35(C), pages 179-188.
    18. Pedram Sendi & Huldrych F Günthard & Mathew Simcock & Bruno Ledergerber & Jörg Schüpbach & Manuel Battegay & for the Swiss HIV Cohort Study, 2007. "Cost-Effectiveness of Genotypic Antiretroviral Resistance Testing in HIV-Infected Patients with Treatment Failure," PLOS ONE, Public Library of Science, vol. 2(1), pages 1-8, January.
    19. Kristensen, Troels & Olsen, Kim Rose & Kilsmark, Jannie & Lauridsen, Jørgen T. & Pedersen, Kjeld Møller, 2012. "Economies of scale and scope in the Danish hospital sector prior to radical restructuring plans," Health Policy, Elsevier, vol. 106(2), pages 120-126.
    20. Karl Claxton & Elisabeth Fenwick & Mark J. Sculpher, 2012. "Decision-making with Uncertainty: The Value of Information," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 51, Edward Elgar Publishing.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tsj:stataj:v:13:y:2013:i:1:p:141-164. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum or Lisa Gilmore (email available below). General contact details of provider: http://www.stata-journal.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.