IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v34y2019i1d10.1007_s00180-018-0829-4.html
   My bibliography  Save this article

SamP2CeT: an interactive computer program for sample size and power calculation for two-level cost-effectiveness trials

Author

Listed:
  • Md Abu Manju

    (Maastricht University)

  • Math J. J. M. Candel

    (Maastricht University)

  • Gerard J. P. van Breukelen

    (Maastricht University)

Abstract

The cost-effectiveness of interventions (e.g. new medical therapies or health care technologies) is often evaluated in randomized clinical trials, where individuals are nested within clusters, for instance patients within general practices. In such two-level cost-effectiveness trials, one can randomly assign treatments to individuals within clusters (multicentre trial) or to entire clusters (cluster randomized trial). Such trials need careful planning to evaluate the cost-effectiveness of interventions within the available research resources. The optimal number of clusters and the optimal number of subjects per cluster for both types of cost-effectiveness trials can be determined by using optimal design theory. However, the construction of the optimal design requires information on model parameters, which may be unknown at the planning stage of a trial. To overcome this problem, a maximin strategy is employed. We have developed a computer program SamP2CeT in R to perform these sample size calculations. SamP2CeT provides a graphical user interface which enables the researchers to optimize the numbers of clusters and subjects per cluster in their cost-effectiveness trial as a function of study costs and outcome variances. In case of insufficient knowledge on model parameters, SamP2CeT also provides safe numbers of clusters and subjects per cluster, based on a maximin strategy. SamP2CeT can be used to calculate the smallest budget needed for a user-specified power level, the largest power attainable with a user-specified budget, and also has the facility to calculate the power for a user-specified design. Recent methodological developments on sample size and power calculation for two-level cost-effectiveness trials have been implemented in SamP2CeT. This program is user-friendly, as illustrated for two published cost-effectiveness trials.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:compst:v:34:y:2019:i:1:d:10.1007_s00180-018-0829-4
    DOI: 10.1007/s00180-018-0829-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00180-018-0829-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00180-018-0829-4?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Andrea Manca & Nigel Rice & Mark J. Sculpher & Andrew H. Briggs, 2005. "Assessing generalisability by location in trial‐based cost‐effectiveness analysis: the use of multilevel models," Health Economics, John Wiley & Sons, Ltd., vol. 14(5), pages 471-485, May.
    2. Richard Grieve & Richard Nixon & Simon G. Thompson & John Cairns, 2007. "Multilevel models for estimating incremental net benefits in multinational studies," Health Economics, John Wiley & Sons, Ltd., vol. 16(8), pages 815-826, August.
    3. Tokola, K. & Larocque, D. & Nevalainen, J. & Oja, H., 2011. "Power, sample size and sampling costs for clustered data," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 852-860, July.
    4. Tom A. B. Snijders & Roel J. Bosker, 1993. "Standard Errors and Sample Sizes for Two-Level Research," Journal of Educational and Behavioral Statistics, , vol. 18(3), pages 237-259, September.
    5. Manuel Gomes & Edmond S.-W. Ng & Richard Grieve & Richard Nixon & James Carpenter & Simon G. Thompson, 2012. "Developing Appropriate Methods for Cost-Effectiveness Analysis of Cluster Randomized Trials," Medical Decision Making, , vol. 32(2), pages 350-361, March.
    6. Aaron A. Stinnett & John Mullahy, 1998. "Net Health Benefits," Medical Decision Making, , vol. 18(2_suppl), pages 68-80, April.
    7. Richard Grieve & Richard Nixon & Simon G. Thompson, 2010. "Bayesian Hierarchical Models for Cost-Effectiveness Analyses that Use Data from Cluster Randomized Trials," Medical Decision Making, , vol. 30(2), pages 163-175, March.
    8. Xiaofeng Liu, 2003. "Statistical Power and Optimum Sample Allocation Ratio for Treatment and Control Having Unequal Costs per Unit of Randomization," Journal of Educational and Behavioral Statistics, , vol. 28(3), pages 231-248, September.
    9. 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.
    10. Bornkamp, Björn & Pinheiro, José & Bretz, Frank, 2009. "MCPMod: An R Package for the Design and Analysis of Dose-Finding Studies," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 29(i07).
    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. 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.
    2. 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).

    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. Moreno, Elías & Girón, F.J. & Vázquez-Polo, F.J. & Negrín, M.A., 2012. "Optimal healthcare decisions: The importance of the covariates in cost–effectiveness analysis," European Journal of Operational Research, Elsevier, vol. 218(2), pages 512-522.
    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. Richard M. Nixon & Simon G. Thompson, 2005. "Methods for incorporating covariate adjustment, subgroup analysis and between‐centre differences into cost‐effectiveness evaluations," Health Economics, John Wiley & Sons, Ltd., vol. 14(12), pages 1217-1229, December.
    5. Moreno, E. & Girón, F.J. & Martínez, M.L. & Vázquez-Polo, F.J. & Negrín, M.A., 2013. "Optimal treatments in cost-effectiveness analysis in the presence of covariates: Improving patient subgroup definition," European Journal of Operational Research, Elsevier, vol. 226(1), pages 173-182.
    6. Jeffrey Hoch & Carolyn Dewa, 2007. "Lessons from Trial-Based Cost-Effectiveness Analyses of Mental Health Interventions," PharmacoEconomics, Springer, vol. 25(10), pages 807-816, October.
    7. Manuel Antonio Espinoza & Andrea Manca & Karl Claxton & Mark Sculpher, 2018. "Social value and individual choice: The value of a choice‐based decision‐making process in a collectively funded health system," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 28-40, February.
    8. A. E. Ades & Karl Claxton & Mark Sculpher, 2006. "Evidence synthesis, parameter correlation and probabilistic sensitivity analysis," Health Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 373-381, April.
    9. 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.
    10. 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.
    11. 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.
    12. Frank G. Sandmann & Julie V. Robotham & Sarah R. Deeny & W. John Edmunds & Mark Jit, 2018. "Estimating the opportunity costs of bed‐days," Health Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 592-605, March.
    13. 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.
    14. 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.
    15. 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.
    16. Emma McIntosh, 2006. "Using Discrete Choice Experiments within a Cost-Benefit Analysis Framework," PharmacoEconomics, Springer, vol. 24(9), pages 855-868, September.
    17. 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.
    18. Jing Voon Chen & Julia L. Higle & Michael Hintlian, 2018. "A systematic approach for examining the impact of calibration uncertainty in disease modeling," Computational Management Science, Springer, vol. 15(3), pages 541-561, October.
    19. Claxton, Karl & Asaria, Miqdad & Chansa, Collins & Jamison, Julian & Lomas, James & Ochalek, Jessica & Paulden, Mike, 2019. "Accounting for timing when assessing health-related policies," LSE Research Online Documents on Economics 100038, London School of Economics and Political Science, LSE Library.
    20. Kari Tokola & Andreas Lundell & Jaakko Nevalainen & Hannu Oja, 2014. "Design and cost optimization for hierarchical data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(2), pages 130-148, 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:spr:compst:v:34:y:2019:i:1:d:10.1007_s00180-018-0829-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.