IDEAS home Printed from https://ideas.repec.org/a/sae/jedbes/v45y2020i4p446-474.html
   My bibliography  Save this article

Optimal Sample Allocation Under Unequal Costs in Cluster-Randomized Trials

Author

Listed:
  • Zuchao Shen

    (University of Florida)

  • Benjamin Kelcey

    (University of Cincinnati)

Abstract

Conventional optimal design frameworks consider a narrow range of sampling cost structures that thereby constrict their capacity to identify the most powerful and efficient designs. We relax several constraints of previous optimal design frameworks by allowing for variable sampling costs in cluster-randomized trials. The proposed framework introduces additional design considerations and has the potential to identify designs with more statistical power, even when some parameters are constrained due to immutable practical concerns. The results also suggest that the gains in efficiency introduced through the expanded framework are fairly robust to misspecifications of the expanded cost structure and concomitant design parameters (e.g., intraclass correlation coefficient). The proposed framework is implemented in the R package odr.

Suggested Citation

  • Zuchao Shen & Benjamin Kelcey, 2020. "Optimal Sample Allocation Under Unequal Costs in Cluster-Randomized Trials," Journal of Educational and Behavioral Statistics, , vol. 45(4), pages 446-474, August.
    • Handle: RePEc:sae:jedbes:v:45:y:2020:i:4:p:446-474
    DOI: 10.3102/1076998620912418
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.3102/1076998620912418
    Download Restriction: no
    File URL: https://libkey.io/10.3102/1076998620912418?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. Connelly, Luke B., 2003. "Balancing the Number and Size of Sites: An Economic Approach to the Optimal Design of Cluster Samples," MPRA Paper 14676, University Library of Munich, Germany.
    2. repec:mpr:mprres:5863 is not listed on IDEAS
    3. Glynn, T.J. & Shopland, D.R. & Manley, M. & Lynn, W.R. & Freedman, L.S. & Green, S.B. & Corle, D.K. & Graubard, B. & Baker, S. & Mills, S.L. & Chapelsky, D.A. & Gail, M. & Mark, S. & Bettinghaus, E. &, 1995. "Community intervention trial for smoking cessation (COMMIT): I. Cohort results from a four-year community intervention," American Journal of Public Health, American Public Health Association, vol. 85(2), pages 183-192.
    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. Mark R. Powell, 2014. "Optimal Food Safety Sampling Under a Budget Constraint," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 93-100, January.
    2. Khanam, Rasheda & Nghiem, Hong Son & Connelly, Luke B., 2009. "Child health and the income gradient: Evidence from Australia," Journal of Health Economics, Elsevier, vol. 28(4), pages 805-817, July.
    3. Takashi Kikuchi & John Gittins, 2010. "A behavioural Bayes approach for sample size determination in cluster randomized clinical trials," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(5), pages 875-888, November.
    4. Chris Schilling & Michelle Tew & Samantha Bunzli & Cade Shadbolt & L. Stefan Lohmander & Zsolt J. Balogh & Francesco Paolucci & Peter F. Choong & Michelle M. Dowsey & Philip Clarke, 2023. "An Economic Model for Estimating Trial Costs with an Application to Placebo Surgery Trials," Applied Health Economics and Health Policy, Springer, vol. 21(2), pages 263-273, March.

    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:4:p:446-474. 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.