IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v36y2009i11p1293-1305.html
   My bibliography  Save this article

Quantile dispersion graphs to compare the efficiencies of cluster randomized designs

Author

Listed:
  • S. Mukhopadhyay
  • S. W. Looney

Abstract

The purpose of this article is to compare efficiencies of several cluster randomized designs using the method of quantile dispersion graphs (QDGs). A cluster randomized design is considered whenever subjects are randomized at a group level but analyzed at the individual level. A prior knowledge of the correlation existing between subjects within the same cluster is necessary to design these cluster randomized trials. Using the QDG approach, we are able to compare several cluster randomized designs without requiring any information on the intracluster correlation. For a given design, several quantiles of the power function, which are directly related to the effect size, are obtained for several effect sizes. The quantiles depend on the intracluster correlation present in the model. The dispersion of these quantiles over the space of the unknown intracluster correlation is determined, and then depicted by the QDGs. Two applications of the proposed methodology are presented.

Suggested Citation

  • S. Mukhopadhyay & S. W. Looney, 2009. "Quantile dispersion graphs to compare the efficiencies of cluster randomized designs," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(11), pages 1293-1305.
    • Handle: RePEc:taf:japsta:v:36:y:2009:i:11:p:1293-1305
    DOI: 10.1080/02664760902914508
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/02664760902914508
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664760902914508?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. Khuri, AndreI. & Lee, Juneyoung, 1998. "A graphical approach for evaluating and comparing designs for nonlinear models," Computational Statistics & Data Analysis, Elsevier, vol. 27(4), pages 433-443, June.
    2. Simpson, J.M. & Klar, N. & Donner, A., 1995. "Accounting for cluster randomization: A review of primary prevention trials, 1990 through 1993," American Journal of Public Health, American Public Health Association, vol. 85(10), pages 1378-1383.
    3. Byoung Cheol Jung & André Khuri & Juneyoung Lee, 2008. "Comparison of designs for the three-fold nested random model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(6), pages 701-715.
    4. Robinson, Kevin S. & Khuri, Andre I., 2003. "Quantile dispersion graphs for evaluating and comparing designs for logistic regression models," Computational Statistics & Data Analysis, Elsevier, vol. 43(1), pages 47-62, May.
    5. A. I. Khuri, 1997. "Quantile dispersion graphs for analysis of variance estimates of variance components," Journal of Applied Statistics, Taylor & Francis Journals, vol. 24(6), pages 711-722.
    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. S.P. Singh & S. Mukhopadhyay & A. Roy, 2015. "Comparison of three-level cluster randomized trials using quantile dispersion graphs," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(8), pages 1792-1812, 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. S.P. Singh & S. Mukhopadhyay & A. Roy, 2015. "Comparison of three-level cluster randomized trials using quantile dispersion graphs," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(8), pages 1792-1812, August.
    2. Jonathan L. Blitstein & Peter J. Hannan & David M. Murray & William R. Shadish, 2005. "Increasing the Degrees of Freedom in Existing Group Randomized Trials," Evaluation Review, , vol. 29(3), pages 241-267, June.
    3. Henry A. Feldman & Sonja M. McKinlay & Minoo Niknian, 1996. "Batch Sampling To Improve Power in a Community Trial," Evaluation Review, , vol. 20(3), pages 244-274, June.
    4. Kadri Ulas Akay, 2014. "A graphical evaluation of logistic ridge estimator in mixture experiments," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(6), pages 1217-1232, June.
    5. Juneyoung Lee & Andre Khuri, 1999. "Graphical technique for comparing designs for random models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 933-947.
    6. Loeza-Serrano, S. & Donev, A.N., 2014. "Construction of experimental designs for estimating variance components," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1168-1177.
    7. Sherri P. Varnell & David M. Murray & William L. Baker, 2001. "An Evaluation of Analysis Options for the One-Group-Per-Condition Design," Evaluation Review, , vol. 25(4), pages 440-453, August.
    8. Robinson, Kevin S. & Khuri, Andre I., 2003. "Quantile dispersion graphs for evaluating and comparing designs for logistic regression models," Computational Statistics & Data Analysis, Elsevier, vol. 43(1), pages 47-62, May.
    9. Paul J. Gruenewald, 1997. "Analysis Approaches To Community Evaluation," Evaluation Review, , vol. 21(2), pages 209-230, April.
    10. Ahn, Chul & Hu, Fan & Skinner, Celette Sugg, 2009. "Effect of imbalance and intracluster correlation coefficient in cluster randomized trials with binary outcomes," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 596-602, January.

    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:taf:japsta:v:36:y:2009:i:11:p:1293-1305. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.