A simple and improved score confidence interval for a single proportion

Yingshu Cao, Ying Xu, Ming T. Tan, Pingyan Chen and Chongyang Duan

Communications in Statistics - Theory and Methods, 2022, vol. 51, issue 8, 2659-2675

Abstract: Confidence interval (CI) for a proportion has been a topic discussed repeatedly in the literature because of its omnipresence in applications. A wide variety of CIs have been proposed since the Wald CI for a proportion performs quite poorly. Among them, the Wilson score interval is widely recommended. However, the Wilson score method suffers from the so-called “downward spikes” when the proportion is close to 0 or 1. Except for the exact methods which ensure the coverage probability be at least the nominal size, the performances of existing proposed methods are similar to the Wilson score CI or its slightly improved version at the cost of increased interval width or computational complexity. In this study, we propose a simple CI which has very good performance in the coverage probability, confidence width, and the location. Especially when the proportion is 80% the CI proposed has a shorter confidence width than the Wilson score method. In combination our new method with the Newcombe’s hybrid way to construct CI for the difference of two independent proportions, we also get a better CI.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2020.1779747 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:51:y:2022:i:8:p:2659-2675

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2020.1779747

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().