IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0007265.html
   My bibliography  Save this article

Analysis of Group Randomized Trials with Multiple Binary Endpoints and Small Number of Groups

Author

Listed:
  • Ji-Hyun Lee
  • Michael J Schell
  • Richard Roetzheim

Abstract

The group randomized trial (GRT) is a common study design to assess the effect of an intervention program aimed at health promotion or disease prevention. In GRTs, groups rather than individuals are randomized into intervention or control arms. Then, responses are measured on individuals within those groups. A number of analytical problems beset GRT designs. The major problem emerges from the likely positive intraclass correlation among observations of individuals within a group. This paper provides an overview of the analytical method for GRT data and applies this method to a randomized cancer prevention trial, where multiple binary primary endpoints were obtained. We develop an index of extra variability to investigate group-specific effects on response. The purpose of the index is to understand the influence of individual groups on evaluating the intervention effect, especially, when a GRT study involves a small number of groups. The multiple endpoints from the GRT design are analyzed using a generalized linear mixed model and the stepdown Bonferroni method of Holm.

Suggested Citation

  • Ji-Hyun Lee & Michael J Schell & Richard Roetzheim, 2009. "Analysis of Group Randomized Trials with Multiple Binary Endpoints and Small Number of Groups," PLOS ONE, Public Library of Science, vol. 4(10), pages 1-9, October.
    • Handle: RePEc:plo:pone00:0007265
    DOI: 10.1371/journal.pone.0007265
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0007265
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0007265&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0007265?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. Varnell, S.P. & Murray, D.M. & Janega, J.B. & Blitstein, J.L., 2004. "Design and Analysis of Group-Randomized Trials: A Review of Recent Practices," American Journal of Public Health, American Public Health Association, vol. 94(3), pages 393-399.
    2. Michael P. Fay & Barry I. Graubard, 2001. "Small-Sample Adjustments for Wald-Type Tests Using Sandwich Estimators," Biometrics, The International Biometric Society, vol. 57(4), pages 1198-1206, December.
    3. Bing Lu & John S. Preisser & Bahjat F. Qaqish & Chirayath Suchindran & Shrikant I. Bangdiwala & Mark Wolfson, 2007. "A Comparison of Two Bias-Corrected Covariance Estimators for Generalized Estimating Equations," Biometrics, The International Biometric Society, vol. 63(3), pages 935-941, September.
    4. Murray, D.M. & Varnell, S.P. & Blitstein, J.L., 2004. "Design and Analysis of Group-Randomized Trials: A Review of Recent Methodological Developments," American Journal of Public Health, American Public Health Association, vol. 94(3), pages 423-432.
    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. Ji-Hyun Lee & William Fulp & Kristen J Wells & Cathy D Meade & Ercilia Calcano & Richard Roetzheim, 2013. "Patient Navigation and Time to Diagnostic Resolution: Results for a Cluster Randomized Trial Evaluating the Efficacy of Patient Navigation among Patients with Breast Cancer Screening Abnormalities, Ta," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-1, September.
    2. Dateng Li & Jing Cao & Song Zhang, 2020. "Power analysis for cluster randomized trials with multiple binary co‐primary endpoints," Biometrics, The International Biometric Society, vol. 76(4), pages 1064-1074, December.

    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. Steven Teerenstra & Bing Lu & John S. Preisser & Theo van Achterberg & George F. Borm, 2010. "Sample Size Considerations for GEE Analyses of Three-Level Cluster Randomized Trials," Biometrics, The International Biometric Society, vol. 66(4), pages 1230-1237, December.
    2. Jonathan L. Blitstein & David M. Murray & Peter J. Hannan & William R. Shadish, 2005. "Increasing the Degrees of Freedom in Future Group Randomized Trials," Evaluation Review, , vol. 29(3), pages 268-286, June.
    3. 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.
    4. repec:mpr:mprres:4632 is not listed on IDEAS
    5. Peter Z. Schochet, "undated". "Statistical Power for Random Assignment Evaluations of Education Programs," Mathematica Policy Research Reports 6749d31ad72d4acf988f7dce5, Mathematica Policy Research.
    6. Benjamin F. Arnold & Francois Rerolle & Christine Tedijanto & Sammy M. Njenga & Mahbubur Rahman & Ayse Ercumen & Andrew Mertens & Amy J. Pickering & Audrie Lin & Charles D. Arnold & Kishor Das & Chris, 2024. "Geographic pair matching in large-scale cluster randomized trials," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    7. Ruoxuan Xiong & Susan Athey & Mohsen Bayati & Guido Imbens, 2019. "Optimal Experimental Design for Staggered Rollouts," Papers 1911.03764, arXiv.org, revised Sep 2023.
    8. Winfried Zinn & Sebastian Sauer & Richard Göllner, 2016. "The German Inpatient Satisfaction Scale," SAGE Open, , vol. 6(2), pages 21582440166, April.
    9. Barry I. Graubard & Thomas R. Fears, 2005. "Standard Errors for Attributable Risk for Simple and Complex Sample Designs," Biometrics, The International Biometric Society, vol. 61(3), pages 847-855, September.
    10. Alexander Robitzsch, 2023. "Linking Error in the 2PL Model," J, MDPI, vol. 6(1), pages 1-27, January.
    11. Siying Guo & Jianxuan Liu & Qiu Wang, 2022. "Effective Learning During COVID-19: Multilevel Covariates Matching and Propensity Score Matching," Annals of Data Science, Springer, vol. 9(5), pages 967-982, October.
    12. Haiyan Wang & Michael Akritas, 2010. "Inference from heteroscedastic functional data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(2), pages 149-168.
    13. Galea, Manuel & de Castro, Mário, 2017. "Robust inference in a linear functional model with replications using the t distribution," Journal of Multivariate Analysis, Elsevier, vol. 160(C), pages 134-145.
    14. van der Laan Mark J. & Petersen Maya & Zheng Wenjing, 2013. "Estimating the Effect of a Community-Based Intervention with Two Communities," Journal of Causal Inference, De Gruyter, vol. 1(1), pages 83-106, June.
    15. Hsiu-Ting Yu & Mark Rooij, 2013. "Model Selection for the Trend Vector Model," Journal of Classification, Springer;The Classification Society, vol. 30(3), pages 338-369, October.
    16. Masahiko Gosho & Hisashi Noma & Kazushi Maruo, 2021. "Practical Review and Comparison of Modified Covariance Estimators for Linear Mixed Models in Small‐sample Longitudinal Studies with Missing Data," International Statistical Review, International Statistical Institute, vol. 89(3), pages 550-572, December.
    17. Hélène Sancho-Garnier & Bruno Pereira & Pierre Césarini, 2012. "A Cluster Randomized Trial to Evaluate a Health Education Programme “Living with Sun at School”," IJERPH, MDPI, vol. 9(7), pages 1-17, July.
    18. Yasaman Jamshidi-Naeini & Armando Pena & Abu Bakkar Siddique & Andrew W. Brown & David B. Allison, 2023. "One Cluster per Condition Is Not a Valid Design in Cluster-Randomized Trials. Comment on Wang et al. The Effect of Different Physical Exercise Programs on Physical Fitness among Preschool Children: A ," IJERPH, MDPI, vol. 20(17), pages 1-2, August.
    19. Raphiel Murden & Jon Agley & Lilian Golzarri-Arroyo & Armando Peña & Danny Valdez & Abu Bakkar Siddique & Moonseong Heo & David B. Allison, 2023. "Comment on Marsigliante et al. Effects on Children’s Physical and Mental Well-Being of a Physical-Activity-Based School Intervention Program: A Randomized Study. Int. J. Environ. Res. Public Health 20," IJERPH, MDPI, vol. 20(23), pages 1-5, December.
    20. Bing Lu & John S. Preisser & Bahjat F. Qaqish & Chirayath Suchindran & Shrikant I. Bangdiwala & Mark Wolfson, 2007. "A Comparison of Two Bias-Corrected Covariance Estimators for Generalized Estimating Equations," Biometrics, The International Biometric Society, vol. 63(3), pages 935-941, September.
    21. Larry V. Hedges, 2009. "Adjusting a Significance Test for Clustering in Designs With Two Levels of Nesting," Journal of Educational and Behavioral Statistics, , vol. 34(4), pages 464-490, December.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0007265. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.