Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/69092
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Type: Journal article
Title: Relative risk estimation in randomized controlled trials: A comparison of methods for independent observations
Author: Yelland, L.
Salter, A.
Ryan, P.
Citation: International Journal of Biostatistics, 2011; 7(1):2-33
Publisher: Berkeley Electronic Press
Issue Date: 2011
ISSN: 1557-4679
1557-4679
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Responsibility: 
Lisa N. Yelland, Amy B. Salter, and Philip Ryan
Abstract: The relative risk is a clinically important measure of the effect of treatment on binary outcomes in randomized controlled trials (RCTs). An adjusted relative risk can be estimated using log binomial regression; however, convergence problems are common with this model. While alternative methods have been proposed for estimating relative risks, comparisons between methods have been limited, particularly in the context of RCTs. We compare ten different methods for estimating relative risks under a variety of scenarios relevant to RCTs with independent observations. Results of a large simulation study show that some methods may fail to overcome the convergence problems of log binomial regression, while others may substantially overestimate the treatment effect or produce inaccurate confidence intervals. Further, conclusions about the effectiveness of treatment may differ depending on the method used. We give recommendations for choosing a method for estimating relative risks in the context of RCTs with independent observations.
Keywords: binary outcome
log binomial regression
randomized controlled trial
relative risk
simulation
Rights: ©2011 Berkeley Electronic Press. All rights reserved.
DOI: 10.2202/1557-4679.1278
Appears in Collections:Aurora harvest
Public Health publications

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