Skip to main content
SpringerLink
Log in

Cluster Randomized Trials

  • Reference work entry
Handbook of Epidemiology

Abstract

A cluster randomized trial is one in which groups of subjects are randomized rather than individuals. They are sometimes known as group randomized trials. This chapter will describe the design and analysis of such trials. Examples of cluster trials in health are given in Box 10.1.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 999.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 1,399.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Alexander N, Emerson P (2005) Analysis of incidence rates in cluster-randomized trials of interventions against recurrent infections, with an application to trachoma. Stat Med 24:2637–2647

    Article  PubMed  Google Scholar 

  • Breslow NE, Clayton DG (1993) Approximate inference in generalized linear mixed models. J Am Stat Assoc 88:125–134

    Google Scholar 

  • Brookmeyer R, Chen Y-Q (1998) Person-time analysis of paired community intervention trials when the number of communities is small. Stat Med 17:2121–2132

    Article  PubMed  CAS  Google Scholar 

  • Campbell MJ (2000) Cluster randomized trials in general (family) practice research. Stat Method Med Res 9:81–94

    Article  CAS  Google Scholar 

  • Campbell MJ (2008) Should we use relative risks or odds ratios in cluster randomized trials with binary outcomes that have high proportions? J Epidemiol Community Health 62(Suppl 1):A24

    Google Scholar 

  • Campbell MJ, Donner A, Klar N (2007) Cluster randomized trials and Statistics in Medicine. Stat Med 26:2–19

    Article  PubMed  CAS  Google Scholar 

  • Campbell MK, Elbourne DR, Altman DG (2004) CONSORT statement: extension to cluster randomized trials. BMJ 328:707–708

    Google Scholar 

  • Carpenter J, Bithell J (2002) Bootstrap confidence intervals: when, which what? A practical guide for medical statisticians. Stat Med 19:1141–1164

    Article  Google Scholar 

  • Clark AB, Bachmann MO (2009) Bayesian methods for analysing cluster randomized trials with count outcome data. Stat Med 29:199–209

    Google Scholar 

  • Davies MJ, Heller S, Skinner TC, Campbell MJ, Carey ME, Cradock S, Dallosso HM, Daly H, Doherty Y, Eaton S, Fox C, Oliver L, Rantell K, Rayman G, Khunti K (2008) Effectiveness of the diabetes education and self management for ongoing and newly diagnosed (DESMOND) programme for people with newly diagnosed type 2 diabetes: cluster randomized controlled trial. Br Med J 336:491–495

    Article  CAS  Google Scholar 

  • Diehr P, Martin DC, Koepsell T, Cheadle A (1995) Breaking the matches in a paired t-test for community interventions when the number of pairs is small. Stat Med 14:1491–1504

    Article  PubMed  CAS  Google Scholar 

  • Donner A, Donald A (1987) Analysis of data arising from a stratified design with the cluster as unit of randomization. Stat Med 6:43–52

    Article  PubMed  CAS  Google Scholar 

  • Donner A, Klar N (2000) Design and analysis of cluster randomization trials. Arnold, London

    Google Scholar 

  • Donner A, Klar N (2004) Pitfalls of and controversies in cluster randomized trials. Am J Public Health 94:416–422

    Article  PubMed Central  PubMed  Google Scholar 

  • Donner A, Birkett N, Buck C (1981) Randomization by cluster: sample size requirements and analysis. Am J Epidemiol 114:906–914

    PubMed  CAS  Google Scholar 

  • Donner A, Taljaard M, Klar N (2007) The merits of breaking the matches in community intervention studies: a cautionary tale. Stat Med 9:2036–2051

    Article  Google Scholar 

  • Efron B, Tibshirani R (1998) An introduction to the bootstrap. CRC Press, Boca Raton/New York/Abingdon

    Google Scholar 

  • Eldridge SM, Ashby D, Feder GS, Rudnicka AR, Ukoumunne OC (2004) Lessons for cluster randomized trials in the twenty-first century: a systematic review of trials in primary care. Clin Trials 1:80–90

    Article  PubMed  Google Scholar 

  • Eldridge S, Kerry S, Ashby D (2006) Sample size for cluster randomized trials: effect of coefficient of variation of cluster size and analysis method. Int J Epidemiol 35:1292–1300

    Article  PubMed  Google Scholar 

  • Eldridge S, Kerry S, Torgerson D (2010) Bias in identifying and recruiting participants in cluster randomised trials: what can be done? BMJ 340:36–39

    Google Scholar 

  • Eldridge S, Kerry S, (2012) A practical guide to cluster randomized trials in Health Service Research. Wiley, Chichester

    Book  Google Scholar 

  • Feldman HA, McKinlay SM (1994) Cohort versus cross-sectional design in large field trials: precision, sample size, and a unifying model. Stat Med 13:61–78

    Article  PubMed  CAS  Google Scholar 

  • Feng Z, Grizzle JE (1992) Correlated binomial variates: properties of estimator of intraclass correlation and its effect on sample size calculation. Stat Med 11:1607–1614

    Article  PubMed  CAS  Google Scholar 

  • Feng Z, McLaran D, Grizzle J (1996) A comparison of statistical methods for clustered data analysis with Gaussian error. Stat Med 15:1793–1806

    Article  PubMed  CAS  Google Scholar 

  • Feng F, Diehr P, Yasui Y, Evans B, Beresford S, Koepsell TD (1999) Explaining community level-variance in group randomized trials. Stat Med 18:539–556

    Article  PubMed  CAS  Google Scholar 

  • Flynn TN, Whitley E, Peters TJ (2002) Recruitment strategies in a cluster randomized trial – cost implications. Stat Med 21:397–405

    Article  PubMed  Google Scholar 

  • Freedman LS, Green SB, Byar DP (1990) Assessing the gain in efficiency due to matching in a community intervention study. Stat Med 9:943–953

    Article  PubMed  CAS  Google Scholar 

  • Friede T, Kieser M (2006) Sample size recalculation in internal pilot study designs: a review. Biom J 48:537–555

    Article  PubMed  Google Scholar 

  • Gail MH, Byar DP, Pechacek TF, Corle DK (1992) Aspects of statistical design for the community intervention trial for smoking cessation (COMMIT). Control Clin Trials 13:6–21

    Article  PubMed  CAS  Google Scholar 

  • Gail MH, Mark SD, Carroll RJ, Green SB, Pee D (1996) On design considerations and randomization-based inference for community intervention trials. Stat Med 15:1069–1092

    Article  PubMed  CAS  Google Scholar 

  • Goldstein H (2002) Multilevel statistical models, 3rd edn. Wiley, Chichester

    Google Scholar 

  • Grosskurth H, Mosha F, Todd J, Mwijarubi E, Klokke A, Senkoro K, Mayaud P, Changalucha J, Nicoll A, Ka-Gina G (1995) Impact of improved treatment of sexually transmitted diseases on HIV infection in rural Tanzania: randomized controlled trial. Lancet 346:530–536

    Article  PubMed  CAS  Google Scholar 

  • Gulliford MC, Adams G, Ukoumunne OC, Latinovic R, Chinn S, Campbell MJ (2005) Intraclass correlation coefficient and outcome prevalence are associated in clustered binary data. J Clin Epidemiol 58:246–251

    Article  PubMed  CAS  Google Scholar 

  • Hayes RJ, Moulton LH (2009) Cluster randomized trials. CRC press, Boca Raton/New York/ Abingdon

    Book  Google Scholar 

  • Heo M, Leon AC (2005) Comparison of statistical methods for analysis of clustered binary observations. Stat Med 24:911–923

    Article  PubMed  Google Scholar 

  • Hsieh FY (1988) Sample size formulae for intervention studies with the cluster as unit of randomization. Stat Med 8:1195–1201

    Article  Google Scholar 

  • Huber PJ, Ronchetti EM (2009) Robust statistics, 2nd edn. Wiley, Hoboken

    Book  Google Scholar 

  • Kerry SM, Bland JM (2001) Unequal cluster sizes for trials in English and Welsh general practice: implications for sample size calculations. Stat Med 20:377–390

    Article  PubMed  CAS  Google Scholar 

  • Kinmonth AL, Woodcock A, Griffin S, Spiegal N, Campbell MJ (1998) Randomized controlled trial of patient centred care of diabetes in general practice: impact on current well being and future disease risk. Br Med J 317:1202–1208

    Article  CAS  Google Scholar 

  • Klar N, Darlington G (2004) Methods for modelling change in cluster randomization trials. Stat Med 23:2341–2357

    Article  PubMed  Google Scholar 

  • Klar N, Donner A (1997) The merits of matching in community intervention trials. Stat Med 16:1753–1764

    Article  PubMed  CAS  Google Scholar 

  • Klar N, Donner A (2001) Current and future challenges in the design and analysis of cluster randomization trials. Stat Med 20:3729–3740

    Article  PubMed  CAS  Google Scholar 

  • Lake S, Kamman E, Klar N, Betensky R (2002) Sample size re-estimation in cluster randomization trials. Stat Med 21:1337–1350

    Article  PubMed  Google Scholar 

  • Lee KJ, Thompson SG (2005) The use of random effects models to allow for clustering in individually randomized trials. Clin Trials 2:163–173

    Article  PubMed  Google Scholar 

  • Lewsey JD (2004) Comparing completely and stratified randomization designs in cluster randomized trials when the stratifying factor is cluster size: a simulation study. Stat Med 23:897–905

    Article  PubMed  CAS  Google Scholar 

  • Liang K-Y, Zeger SL (1986) Longitudinal data analysis using generalized linear models. Biometrika 73:13–22

    Article  Google Scholar 

  • Loeys T, Vansteelandt S, Goetghbeur E (2001) Accounting for correlation and compliance in cluster randomized trials. Stat Med 20:3753–3767

    Article  PubMed  CAS  Google Scholar 

  • Machin D, Campbell MJ, Tan S-B, Tan S-H (2008) Statistical tables for the design of clinical studies. Wiley-Blackwell, Chichester

    Book  Google Scholar 

  • Mancl L, DeRouen TA (2001) A covariance estimator for GEE with improved small sample properties. Biometrics 57:126–134

    Article  PubMed  CAS  Google Scholar 

  • Martin DC, Diehr P, Perrin EB, Koepsell TD (1993) The effect of matching on the power of randomized community intervention studies. Stat Med 12:329–338

    Article  PubMed  CAS  Google Scholar 

  • Matthews JNS, Altman DG, Campbell MJ, Royston P (1990) Analysis of serial data using summary measures. Br Med J 300:230–235

    Article  CAS  Google Scholar 

  • Moerbeek M (2006) Power and money in cluster randomized trials: when is it worth measuring a covariate? Stat Med 25:2607–2617

    Article  PubMed  Google Scholar 

  • Mills S, Campbell MJ, Waters WE (1986) Public knowledge of AIDS and the DHSS advertisement campaign. Br Med J 293:1089–1090

    Article  CAS  Google Scholar 

  • Murray DM (1998) The design and analysis of group-randomized trials. Oxford University Press, Oxford

    Google Scholar 

  • Murray DM, Vernell SP, Blitstein JL (2004) Design and analysis of group-randomized trials: a review of recent methodological developments. Am J Public Health 94:423–432

    Article  PubMed Central  PubMed  Google Scholar 

  • Neuhaus JM, Jewell NP (1993) A geometric approach to assess bias due to omitted covariates in generalized liner models. Biometrika 80:807–815

    Article  Google Scholar 

  • Nixon RM, Thompson SG (2003) Baseline adjustments for binary data in repeated cross-sectional cluster randomized trials. Stat Med 22:2673–2692

    Article  PubMed  CAS  Google Scholar 

  • Pan W, Wall MM (2002) Small sample adjustments in using the sandwich variance estimator in generalized estimating equations. Stat Med 21:1429–1441

    Article  PubMed  Google Scholar 

  • Preisser JJ, Young ML, Zaccaro DJ, Wolfson M (2003) An integrated population average approach to the design, analysis and sample size determination of cluster unit trials. Stat Med 22:1235–1254

    Article  PubMed  Google Scholar 

  • Roberts C, Roberts SA (2002) Design and analysis of clinical trials with clustering effects due to treatment. Clin Trials 2:152–162

    Article  Google Scholar 

  • Soncini JA, Maserejian N, Trachtenberg F, Tavares M, Hayes C (2007) The longevity of amalgam versus compomer/composite restorations in posterior primary and permanent teeth. J Am Dent Assoc 138:763–772

    Article  PubMed  Google Scholar 

  • Spiegelhalter DJ (2001) Bayesian methods for cluster randomized trials with continuous response. Stat Med 20:435–452

    Article  PubMed  CAS  Google Scholar 

  • Statacorp (2009) Stata release 11. Statistical software. Statacorp LP, College Station

    Google Scholar 

  • Thompson C, Kinmonth AL, Stevens L, Peveler R, Stevens R, Ostler K, Pickering RM, Baker NG, Henson A, Preece J, Cooper D, Campbell MJ (2000) Effects of a clinical practice guideline and practice based education on the detection and outcome of depression in primary care: Hampshire depression project randomised controlled trial. Lancet 355:185–191

    Article  PubMed  CAS  Google Scholar 

  • Thompson SG, Pyke S, Hardy RJ (1997) The design and analysis of paired cluster randomized trials: an application of meta-analysis techniques. Stat Med 16:2063–2980

    Article  PubMed  CAS  Google Scholar 

  • Thompson SG, Warn DE, Turner RM (2004) Bayesian methods for analysis of binary outcome data in cluster randomized trials on the absolute risk scale. Stat Med 23:389–410

    Article  PubMed  Google Scholar 

  • Turner RM, Omar RZ, Thompson SG (2001) Bayesian methods of analysis for cluster randomized trials with binary outcome data. Stat Med 20:453–472

    Article  PubMed  CAS  Google Scholar 

  • Turner RM, Prevost AT, Thompson SG (2004) Allowing for imprecision of the intracluster correlation coefficient in the design of cluster randomized trials. Stat Med 23:1195–1214

    Article  PubMed  Google Scholar 

  • Ukoumunne OC, Thompson SG (2001) Analysis of cluster randomized trials with repeated cross-sectional binary measurements. Stat Med 20:417–433

    Article  PubMed  CAS  Google Scholar 

  • Ukoumunne OC, Carlin JB, Gulliford MC (2007) A simulation study of odds ratio estimation for binary outcomes from cluster randomized trials. Stat Med 26:3415–3428

    Article  PubMed  Google Scholar 

  • Ukoumunne OC, Forbes AB, Carlin JB, Gulliford MC (2008) Comparison of the risk difference, risk ratio and odds ratio scales for quantifying the unadjusted intervention effect in cluster randomized trials. Stat Med 27:5143–5155

    Article  PubMed  Google Scholar 

  • Wight DG, Raab GM, Henderson M, Abraham C, Buston K, Hart G, Scott S (2002) Limits of teacher delivered sex education: interim behavioural outcomes from randomized trial. Br Med J 324:1430–1433

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

    Authors
    1. Michael J. Campbell
      View author publications

      You can also search for this author in PubMed Google Scholar

    Editor information

    Editors and Affiliations

    1. Department of Epidemiological Methods and Etiologic Research, Leibniz Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany

      Wolfgang Ahrens

    2. Department of Biometry and Data Management, Leibniz Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany

      Iris Pigeot

    Rights and permissions

    Reprints and permissions

    Copyright information

    © 2014 Springer Science+Business Media New York

    About this entry

    Cite this entry

    Campbell, M.J. (2014). Cluster Randomized Trials. In: Ahrens, W., Pigeot, I. (eds) Handbook of Epidemiology. Springer, New York, NY. https://doi.org/10.1007/978-0-387-09834-0_47

    Download citation

    • DOI: https://doi.org/10.1007/978-0-387-09834-0_47

    • Publisher Name: Springer, New York, NY

    • Print ISBN: 978-0-387-09833-3

    • Online ISBN: 978-0-387-09834-0

    • eBook Packages: MedicineReference Module Medicine

    Publish with us

    Policies and ethics

    Search

    Navigation