Confidence intervals for a difference between proportions based on paired data
Correction(s) for this article
-
Correction
- Volume 29Issue 20Statistics in Medicine
- pages: 2168-2168
- First Published online: May 20, 2010
Corresponding Author
Man-Lai Tang
Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, People's Republic of China
Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, People's Republic of ChinaSearch for more papers by this authorMan-Ho Ling
Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, People's Republic of China
Search for more papers by this authorLeevan Ling
Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, People's Republic of China
Search for more papers by this authorGuoliang Tian
Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong Kong, People's Republic of China
Search for more papers by this authorCorresponding Author
Man-Lai Tang
Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, People's Republic of China
Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, People's Republic of ChinaSearch for more papers by this authorMan-Ho Ling
Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, People's Republic of China
Search for more papers by this authorLeevan Ling
Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, People's Republic of China
Search for more papers by this authorGuoliang Tian
Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong Kong, People's Republic of China
Search for more papers by this authorAbstract
We construct several explicit asymptotic two-sided confidence intervals (CIs) for the difference between two correlated proportions using the method of variance of estimates recovery (MOVER). The basic idea is to recover variance estimates required for the proportion difference from the confidence limits for single proportions. The CI estimators for a single proportion, which are incorporated with the MOVER, include the Agresti–Coull, the Wilson, and the Jeffreys CIs. Our simulation results show that the MOVER-type CIs based on the continuity corrected Φ coefficient and the Tango score CI perform satisfactory in small sample designs and spare data structures. We illustrate the proposed CIs with several real examples. Copyright © 2009 John Wiley & Sons, Ltd.
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