Journal
STATISTICS IN MEDICINE
Volume 32, Issue 24, Pages 4162-4179Publisher
WILEY
DOI: 10.1002/sim.5819
Keywords
cluster randomized; generalized estimating equations; multisite; Poisson regression
Categories
Funding
- National Institute of Mental Health [R01 MH 084855, P50 MH074678]
Ask authors/readers for more resources
We consider the problem of sample size determination for count data. Such data arise naturally in the context of multicenter (or cluster) randomized clinical trials, where patients are nested within research centers. We consider cluster-specific and population-averaged estimators (maximum likelihood based on generalized mixed-effect regression and generalized estimating equations, respectively) for subject-level and cluster-level randomized designs, respectively. We provide simple expressions for calculating the number of clusters when comparing event rates of two groups in cross-sectional studies. The expressions we derive have closed-form solutions and are based on either between-cluster variation or intercluster correlation for cross-sectional studies. We provide both theoretical and numerical comparisons of our methods with other existing methods. We specifically show that the performance of the proposed method is better for subject-level randomized designs, whereas the comparative performance depends on the rate ratio for the cluster-level randomized designs. We also provide a versatile method for longitudinal studies. Three real data examples illustrate the results. Copyright (c) 2013 John Wiley & Sons, Ltd.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available