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Abstract Details
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Activity Number:
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82
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Type:
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Contributed
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Date/Time:
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Sunday, July 31, 2011 : 4:00 PM to 5:50 PM
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Sponsor:
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ENAR
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| Abstract - #303027 |
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Title:
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Comparison of 95% Confidence Interval for Intra-Cluster Correlation Estimates for Clustered Binary Data
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Author(s):
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Hrishikesh Chakraborty*+
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Companies:
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RTI International
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Address:
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, , ,
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Keywords:
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ICC ;
95% CI
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Abstract:
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Several methods have been proposed to estimate the 95% confidence interval (CI) for intra-cluster correlation coefficient (ICC) for clustered binary data. We developed a new method to estimate 95% CI of ICC for clustered binary data that utilizes a multinomial approach, using re-sampling methods and U-statistics. To compare the 95% CI estimates from different methods for different settings, we created simulated datasets using Monte Carlo simulation, varying numerous inputs such as outcome proportion, cluster size, and number of clusters, and calculated 95% CI estimates of ICC using these data. We found that the 95% CI of ICC provided by ANOVA and our newly developed multinomial method estimates are good estimates for varying proportions, proportion variations, cluster sizes, cluster size variations, and number of clusters.
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