IDEAS home Printed from https://ideas.repec.org/a/sae/jedbes/v45y2020i6p690-718.html
   My bibliography  Save this article

Power Analysis for Two-Level Multisite Randomized Cost-Effectiveness Trials

Author

Listed:
  • Wei Li

    (8063University of Alabama)

  • Nianbo Dong

    (2331University of North Carolina at Chapel Hill)

  • Rebecca A. Maynard

    (6572University of Pennsylvania)

Abstract

Cost-effectiveness analysis is a widely used educational evaluation tool. The randomized controlled trials that aim to evaluate the cost-effectiveness of the treatment are commonly referred to as randomized cost-effectiveness trials (RCETs). This study provides methods of power analysis for two-level multisite RCETs. Power computations take account of sample sizes, the effect size, covariates effects, nesting effects for both cost and effectiveness measures, the ratio of the total variance of the cost measure to the total variance of effectiveness measure, and correlations between cost and effectiveness measures at each level. Illustrative examples that show how power is influenced by the sample sizes, nesting effects, covariate effects, and correlations between cost and effectiveness measures are presented. We also demonstrate how the calculations can be applied in the design phase of two-level multisite RCETs using the software PowerUp!-CEA (Version 1.0).

Suggested Citation

  • Wei Li & Nianbo Dong & Rebecca A. Maynard, 2020. "Power Analysis for Two-Level Multisite Randomized Cost-Effectiveness Trials," Journal of Educational and Behavioral Statistics, , vol. 45(6), pages 690-718, December.
    • Handle: RePEc:sae:jedbes:v:45:y:2020:i:6:p:690-718
    DOI: 10.3102/1076998620911916
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.3102/1076998620911916
    Download Restriction: no
    File URL: https://libkey.io/10.3102/1076998620911916?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Mustafa, Nasreen, 2018. "Cost-effectiveness analysis: Educational interventions that reduce the incidence of HIV/AIDS infection in Kenyan teenagers," International Journal of Educational Development, Elsevier, vol. 62(C), pages 264-269.
    2. Herrera-Araujo, Daniel & Shaywitz, Bennett A. & Holahan, John M. & Marchione, Karen E. & Michaels, Reissa & Shaywitz, Sally E. & Hammitt, James K., 2017. "Evaluating Willingness to Pay as a Measure of the Impact of Dyslexia in Adults," Journal of Benefit-Cost Analysis, Cambridge University Press, vol. 8(1), pages 24-48, April.
    3. Aaron A. Stinnett & John Mullahy, 1998. "Net Health Benefits," Medical Decision Making, , vol. 18(2_suppl), pages 68-80, April.
    4. Md Abu Manju & Math J. J. M. Candel & Gerard J. P. van Breukelen, 2019. "SamP2CeT: an interactive computer program for sample size and power calculation for two-level cost-effectiveness trials," Computational Statistics, Springer, vol. 34(1), pages 47-70, March.
    5. Kyle Cox & Benjamin Kelcey, 2019. "Optimal Design of Cluster- and Multisite-Randomized Studies Using Fallible Outcome Measures," Evaluation Review, , vol. 43(3-4), pages 189-225, June.
    6. Aaron A. Stinnett & John Mullahy, 1998. "Net Health Benefits: A New Framework for the Analysis of Uncertainty in Cost-Effectiveness Analysis," NBER Technical Working Papers 0227, National Bureau of Economic Research, Inc.
    7. repec:mpr:mprres:5863 is not listed on IDEAS
    8. Patrick J. Wolf & Michael McShane, 2013. "Is the Juice Worth the Squeeze? A Benefit/Cost Analysis of the District of Columbia Opportunity Scholarship Program," Education Finance and Policy, MIT Press, vol. 8(1), pages 74-99, January.
    Full references (including those not matched with items on IDEAS)

    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. 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. Basu, Anirban & Jena, Anupam B. & Philipson, Tomas J., 2011. "The impact of comparative effectiveness research on health and health care spending," Journal of Health Economics, Elsevier, vol. 30(4), pages 695-706, July.
    3. Simon Eckermann & Tim Coelli, 2008. "Including quality attributes in a model of health care efficiency: A net benefit approach," CEPA Working Papers Series WP032008, School of Economics, University of Queensland, Australia.
    4. Clarke, Philip M. & Hayes, Alison J., 2009. "Measuring achievement: Changes in risk factors for cardiovascular disease in Australia," Social Science & Medicine, Elsevier, vol. 68(3), pages 552-561, February.
    5. Niklas Zethraeus & Magnus Johannesson & Bengt Jönsson & Mickael Löthgren & Magnus Tambour, 2003. "Advantages of Using the Net-Benefit Approach for Analysing Uncertainty in Economic Evaluation Studies," PharmacoEconomics, Springer, vol. 21(1), pages 39-48, January.
    6. Jordan Amdahl & Jose Diaz & Arati Sharma & Jinhee Park & David Chandiwana & Thomas E Delea, 2017. "Cost-effectiveness of pazopanib versus sunitinib for metastatic renal cell carcinoma in the United Kingdom," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-18, June.
    7. Emma McIntosh, 2006. "Using Discrete Choice Experiments within a Cost-Benefit Analysis Framework," PharmacoEconomics, Springer, vol. 24(9), pages 855-868, September.
    8. Martin Henriksson & Fredrik Lundgren & Per Carlsson, 2006. "Informing the efficient use of health care and health care research resources ‐ the case of screening for abdominal aortic aneurysm in Sweden," Health Economics, John Wiley & Sons, Ltd., vol. 15(12), pages 1311-1322, December.
    9. David Brain & Ruth Tulleners & Xing Lee & Qinglu Cheng & Nicholas Graves & Rosana Pacella, 2019. "Cost-effectiveness analysis of an innovative model of care for chronic wounds patients," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-13, March.
    10. Stefano Conti & Karl Claxton, 2008. "Dimensions of design space: a decision-theoretic approach to optimal research design," Working Papers 038cherp, Centre for Health Economics, University of York.
    11. Andrew H. Briggs & Bernie J. O'Brien, 2001. "The death of cost‐minimization analysis?," Health Economics, John Wiley & Sons, Ltd., vol. 10(2), pages 179-184, March.
    12. 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.
    13. 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.
    14. John Mullahy, 2017. "Individual Results May Vary: Elementary Analytics of Inequality-Probability Bounds, with Applications to Health-Outcome Treatment Effects," NBER Working Papers 23603, National Bureau of Economic Research, Inc.
    15. 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.
    16. Bas Groot Koerkamp & M. G. Myriam Hunink & Theo Stijnen & Milton C. Weinstein, 2006. "Identifying key parameters in cost‐effectiveness analysis using value of information: a comparison of methods," Health Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 383-392, April.
    17. Quang Dang Nguyen & Mikhail Prokopenko, 2022. "A general framework for optimising cost-effectiveness of pandemic response under partial intervention measures," Papers 2205.08996, arXiv.org, revised Nov 2022.
    18. Mullahy, John, 2018. "Individual results may vary: Inequality-probability bounds for some health-outcome treatment effects," Journal of Health Economics, Elsevier, vol. 61(C), pages 151-162.
    19. Pauline Chauvin & Jean-Michel Josselin & Denis Heresbach, 2012. "Incremental net benefit and acceptability of alternative health policies: a case study of mass screening for colorectal cancer," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(3), pages 237-250, June.
    20. Elamin H. Elbasha, 2005. "Risk aversion and uncertainty in cost‐effectiveness analysis: the expected‐utility, moment‐generating function approach," Health Economics, John Wiley & Sons, Ltd., vol. 14(5), pages 457-470, May.

    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:sae:jedbes:v:45:y:2020:i:6:p:690-718. 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: SAGE Publications (email available below). General contact details of provider: .

    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.