Literature DB >> 11343359

Statistical models appropriate for designs often used in group-randomized trials.

D M Murray1.   

Abstract

Group-randomized trials are characterised by the allocation of identifiable groups rather than individuals to study conditions; members within those groups are then observed to assess the effect of the intervention. It is convenient to categorize the designs employed in group-randomized trials along two dimensions, each with two levels. The first distinguishes between designs having just one or two time intervals and those having three or more intervals. The second distinguishes between nested cohort and nested cross-sectional designs. Following a brief review of the design and analytic issues common to group-randomized trials, and their general solutions, this paper presents the adaptations of the mixed-model analysis of covariance and random coefficients models that are required for the four combinations that result from this categorization scheme. The assumptions, strengths and weaknesses of each model are discussed. Copyright 2001 John Wiley & Sons, Ltd.

Mesh:

Year:  2001        PMID: 11343359     DOI: 10.1002/sim.675

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  18 in total

1.  Why don't we see more translation of health promotion research to practice? Rethinking the efficacy-to-effectiveness transition.

Authors:  Russell E Glasgow; Edward Lichtenstein; Alfred C Marcus
Journal:  Am J Public Health       Date:  2003-08       Impact factor: 9.308

2.  Bias.

Authors:  Miguel Delgado-Rodríguez; Javier Llorca
Journal:  J Epidemiol Community Health       Date:  2004-08       Impact factor: 3.710

Review 3.  Design and analysis of group-randomized trials: a review of recent methodological developments.

Authors:  David M Murray; Sherri P Varnell; Jonathan L Blitstein
Journal:  Am J Public Health       Date:  2004-03       Impact factor: 9.308

4.  The multilevel structure of four adolescent problems.

Authors:  Keith Smolkowski; Anthony Biglan; Clyde Dent; John Seeley
Journal:  Prev Sci       Date:  2006-09

5.  Design and rationale for evaluating salad bars and students' fruit and vegetable consumption: A cluster randomized factorial trial with objective assessments.

Authors:  Marc A Adams; Punam Ohri-Vachaspati; Timothy J Richards; Michael Todd; Meg Bruening
Journal:  Contemp Clin Trials       Date:  2018-12-18       Impact factor: 2.226

6.  Ethical challenges in cluster randomized controlled trials: experiences from public health interventions in Africa and Asia.

Authors:  David Osrin; Kishwar Azad; Armida Fernandez; Dharma S Manandhar; Charles W Mwansambo; Prasanta Tripathy; Anthony M Costello
Journal:  Bull World Health Organ       Date:  2009-10       Impact factor: 9.408

7.  Kalèdo, a new educational board-game, gives nutritional rudiments and encourages healthy eating in children: a pilot cluster randomized trial.

Authors:  Salvatore Amaro; Alessandro Viggiano; Anna Di Costanzo; Ida Madeo; Andrea Viggiano; Maria Ena Baccari; Elena Marchitelli; Maddalena Raia; Emanuela Viggiano; Sunil Deepak; Marcellino Monda; Bruno De Luca
Journal:  Eur J Pediatr       Date:  2006-05-30       Impact factor: 3.183

8.  Kaledo, a board game for nutrition education of children and adolescents at school: cluster randomized controlled trial of healthy lifestyle promotion.

Authors:  Alessandro Viggiano; Emanuela Viggiano; Anna Di Costanzo; Andrea Viggiano; Eleonora Andreozzi; Vincenzo Romano; Ines Rianna; Claudia Vicidomini; Giuliana Gargano; Lucia Incarnato; Celeste Fevola; Pietro Volta; Caterina Tolomeo; Giuseppina Scianni; Caterina Santangelo; Roberta Battista; Marcellino Monda; Adela Viggiano; Bruno De Luca; Salvatore Amaro
Journal:  Eur J Pediatr       Date:  2014-07-22       Impact factor: 3.183

Review 9.  Design and analysis of group-randomized trials in cancer: A review of current practices.

Authors:  David M Murray; Sherri L Pals; Stephanie M George; Andrey Kuzmichev; Gabriel Y Lai; Jocelyn A Lee; Ranell L Myles; Shakira M Nelson
Journal:  Prev Med       Date:  2018-03-16       Impact factor: 4.018

10.  Optimal combination of estimating equations in the analysis of multilevel nested correlated data.

Authors:  J A Stoner; B G Leroux; M Puumala
Journal:  Stat Med       Date:  2010-02-20       Impact factor: 2.373

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