Determining the sample size for a cluster-randomised trial: Bayesian hierarchical modelling of the ICC estimate

Tishkovskaya, Svetlana orcid iconORCID: 0000-0003-3087-6380, Sutton, Chris J orcid iconORCID: 0000-0002-6406-1318, Thomas, Lois Helene orcid iconORCID: 0000-0001-5218-6546, Leathley, Michael John and Watkins, Caroline Leigh orcid iconORCID: 0000-0002-9403-3772 (2015) Determining the sample size for a cluster-randomised trial: Bayesian hierarchical modelling of the ICC estimate. In: 3rd International Clinical Trials Methodology Conference, 16-17 November 2015, Glasgow.

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Official URL: http://dx.doi.org/10.1186/1745-6215-16-S2-P229

Abstract

In common with many cluster-randomised trials, it was difficult to determine the appropriate sample size for the planned trial of the effectiveness of a systematic voiding programme for post-stroke incontinence due to the lack of a robust estimate of the intra-cluster correlation coefficient (ICC). One approach to overcome this problem is a method of combining ICC values in the Bayesian framework (Turner et al. 2005). We adopted this approach and used Bayesian hierarchical modelling to estimate the ICC.


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