Design and analysis of group-randomized trials in cancer prevention and control.

Murray, Dennis; S, Pals; Blitstein, Jonathan

doi:10.1037/14499-005

Cited by 56 publications

(85 citation statements)

References 51 publications

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“…22 Unadjusted and adjusted models were run for each type of physical activity resource (i.e., churches, parks, schools, commercial facilities). Covariates in the adjusted models included race, parent education, BMI, and median household income.…”

Section: Statistical Analysesmentioning

confidence: 99%

Physical Activity and Neighborhood Resources in High School Girls

Pate

Colabianchi

Porter

et al. 2008

American Journal of Preventive Medicine

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Section: Statistical Analysesmentioning

confidence: 99%

Physical Activity and Neighborhood Resources in High School Girls

Pate

Colabianchi

Porter

et al. 2008

American Journal of Preventive Medicine

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“…To improve the validity, as well as the precision, of our estimates, 20 we controlled for individual, family, and community characteristics. The villages also underwent substantial socioeconomic changes during the 25 years that elapsed between the original intervention and the survey in 2002.…”

Section: Potentially Confounding Variablesmentioning

confidence: 99%

Effect of a nutrition intervention during early childhood on economic productivity in Guatemalan adults

et al. 2008

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“…Note again that published analyses of conventional trials typically neglect to take account of the surgeon (or, in general, clinician) effect. The observations can be thought of as having a clustered data structure [9][10][11].…”

Section: Model Developmentmentioning

confidence: 99%

Statistical issues in the design and analysis of expertise‐based randomized clinical trials

Walter

Ismaila

Devereaux

2008

Statistics in Medicine

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SUMMARYIn order to avoid certain difficulties with the conventional randomized clinical trial design, the expertise-based design has been proposed as an alternative. In the expertise-based design, patients are randomized to clinicians (e.g. surgeons), who then treat all their patients with their preferred intervention. This design recognizes individual clinical preferences and so may reduce the rates of procedural crossovers compared with the conventional design. It may also facilitate recruitment of clinicians, because they are always allowed to deliver their therapy of choice, a feature that may also be attractive to patients.The expertise-based design avoids the possibility of so-called differential expertise bias. If a standard treatment is generally more familiar to clinicians than a new experimental treatment, then in the conventional design, more patients randomized to the standard treatment will have an expert clinician, compared with patients randomized to the experimental treatment. If expertise affects the study outcome, then a biased comparison of the treatment groups will occur.We examined the relative efficiency of estimating the treatment effect in the expertise-based and conventional designs. We recognize that expected patient outcomes may be better in the expertisebased design, which in turn may modify the estimated treatment effect. In particular, a larger treatment effect in the expertise-based design can sometimes offset a higher standard error arising from the confounding of clinician effects with treatments.These concepts are illustrated with data taken from a randomized trial of two alternative surgical techniques for tibial fractures.

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Design and analysis of group-randomized trials in cancer prevention and control.

Cited by 56 publications

References 51 publications

Physical Activity and Neighborhood Resources in High School Girls

Physical Activity and Neighborhood Resources in High School Girls

Effect of a nutrition intervention during early childhood on economic productivity in Guatemalan adults

Statistical issues in the design and analysis of expertise‐based randomized clinical trials

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