Literature DB >> 10946428

Cluster randomized trials in general (family) practice research.

M J Campbell1.   

Abstract

Cluster randomized trials are increasingly common in general practice (family medicine). This paper will consider the design and analysis of such trials and emphasize the similarities and differences with trials in education, heath promotion and public health. Issues discussed are the estimation and range of values of the intra-cluster correlation coefficient found in general practice, and the associated sample size problems. There are problems with widely varying numbers of subjects per cluster, which leads to planning and analysis difficulties. Ethical issues in these trials, and considerations such as the principle of intention to treat are also considered. An example of the type of analysis available for a continuous outcome variable is given, and the available software is summarized briefly.

Mesh:

Year:  2000        PMID: 10946428     DOI: 10.1177/096228020000900202

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  41 in total

1.  Impact of the CSM advice on thioridazine on general practitioner prescribing behaviour in Leeds: time series analysis.

Authors:  Nat M J Wright; Alison J Roberts; Victoria L Allgar; Charlotte N E Tompkins; Darren C Greenwood; Gillian Laurence
Journal:  Br J Gen Pract       Date:  2004-05       Impact factor: 5.386

2.  Extending CONSORT to include cluster trials.

Authors:  Michael J Campbell
Journal:  BMJ       Date:  2004-03-20

3.  Pitfalls of and controversies in cluster randomization trials.

Authors:  Allan Donner; Neil Klar
Journal:  Am J Public Health       Date:  2004-03       Impact factor: 9.308

4.  Informed consent and cluster-randomized trials.

Authors:  Julius Sim; Angus Dawson
Journal:  Am J Public Health       Date:  2012-01-19       Impact factor: 9.308

Review 5.  Best (but oft-forgotten) practices: designing, analyzing, and reporting cluster randomized controlled trials.

Authors:  Andrew W Brown; Peng Li; Michelle M Bohan Brown; Kathryn A Kaiser; Scott W Keith; J Michael Oakes; David B Allison
Journal:  Am J Clin Nutr       Date:  2015-05-27       Impact factor: 7.045

6.  Small sample performance of bias-corrected sandwich estimators for cluster-randomized trials with binary outcomes.

Authors:  Peng Li; David T Redden
Journal:  Stat Med       Date:  2014-10-24       Impact factor: 2.373

Review 7.  Immediate versus delayed postpartum insertion of contraceptive implant for contraception.

Authors:  Jen Sothornwit; Yuthapong Werawatakul; Srinaree Kaewrudee; Pisake Lumbiganon; Malinee Laopaiboon
Journal:  Cochrane Database Syst Rev       Date:  2017-04-22

8.  The Chronic CARe for diAbeTes study (CARAT): a cluster randomized controlled trial.

Authors:  Anja Frei; Corinne Chmiel; Hansueli Schläpfer; Beatrice Birnbaum; Ulrike Held; Johann Steurer; Thomas Rosemann
Journal:  Cardiovasc Diabetol       Date:  2010-06-15       Impact factor: 9.951

9.  Personal digital assistants to collect tuberculosis bacteriology data in Peru reduce delays, errors, and workload, and are acceptable to users: cluster randomized controlled trial.

Authors:  Joaquín A Blaya; Ted Cohen; Pablo Rodríguez; Jihoon Kim; Hamish S F Fraser
Journal:  Int J Infect Dis       Date:  2008-12-18       Impact factor: 3.623

10.  Comparison of Bayesian and classical methods in the analysis of cluster randomized controlled trials with a binary outcome: the Community Hypertension Assessment Trial (CHAT).

Authors:  Jinhui Ma; Lehana Thabane; Janusz Kaczorowski; Larry Chambers; Lisa Dolovich; Tina Karwalajtys; Cheryl Levitt
Journal:  BMC Med Res Methodol       Date:  2009-06-16       Impact factor: 4.615

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