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Krishna Saha

Central Connecticut State University



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Daniel Miller

Central Connecticut State University



29 – Confidence Interval and Band Estimation

On Confidence Intervals for a Single Proportion in the Analysis of CTC Images Data

Sponsor: Biometrics Section
Keywords: beta-binomial, clustered binary data, CTC images data, confidence interval, proportion

Krishna Saha

Central Connecticut State University

Daniel Miller

Central Connecticut State University

In the estimation of sensitivity and specificity in diagnostic medicine when a patient or the diagnostic unit is considered as a cluster, the confidence interval of a single proportion is frequently used. A number of confidence intervals for a single proportion in the case of non-clustered binary data are proposed in the literature and implemented in standard software packages. However, little attention has been paid to extending such inferences using clustered binary data. In this study, we consider several asymptotic procedures, based on parametric and semiparametric models, to construct the confidence interval for a single proportion based on binary outcome data arising in cluster studies. We compare the performance of the five proposed methods, in terms of coverage and expected lengths, with a Monte Carlo simulation study and we illustrate the methodology with an example from the CTC images study.

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