Letter to the Editor: A novel confidence interval for a single proportion in the presence of clustered binary outcome data (SMMR, 2019)
Author:
Affiliation:
1. School of Computer and Information Engineering, Zhejiang Gongshang University, Hangzhou, China
2. School of Community Health Sciences, University of Nevada Las Vegas, Las Vegas, NV, USA
Publisher
SAGE Publications
Subject
Health Information Management,Statistics and Probability,Epidemiology
Link
http://journals.sagepub.com/doi/pdf/10.1177/0962280219840056
Reference4 articles.
1. Efficient tests for one sample correlated binary data with applications
2. Exact Methods for Testing the Equality of Proportions for Binary Clustered Data From Otolaryngologic Studies
3. Exact confidence limits for the response rate in two-stage designs with over- or under-enrollment in the second stage
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