Abstract Details
Activity Number:
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652
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Type:
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Contributed
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Date/Time:
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Thursday, August 13, 2015 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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Abstract #316209
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View Presentation
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Title:
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Exact Methods of Testing the Homogeneity of Prevalence for Binary Correlated Data
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Author(s):
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Xiaobin Liu* and Changxing Ma and Song Liu and Zhengyu Yang
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Companies:
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SUNY Buffalo and SUNY Buffalo and Roswell Park Cancer Institute and SUNY Buffalo
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Keywords:
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Binary correlated data ;
Equal correlation coefficients model ;
Small sample ;
Exact tests ;
the M approach ;
the E+M approach
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Abstract:
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Binary correlated data arise in many clinical trials. To test the homogeneity of prevalence proportions among different groups is an important issue when conducting these trials. The equal correlation coefficients model proposed by Donner(1989) is a popular model to deal with data with binary correlated pattern. The asymptotic chi-square test works well when the sample sizes are large. However, it would fail to maintain the type I error rate when the sample sizes are relatively small. In this paper, we propose several exact methods to deal with small sample scenarios. Their performances are compared with respect to type I error rate and power. The M approach and the E+M approach seem to outperform the others. A real work example is given to further explain how these approaches work. Finally, the computational efficiency of the exact methods is discussed as a pressing issue of future work.
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Authors who are presenting talks have a * after their name.
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