Asymptotic two-tailed confidence intervals for the difference of proportions
A. Mart�n Andr�s,
M. Álvarez Hernández and
I. Herranz Tejedor
Journal of Applied Statistics, 2012, vol. 39, issue 7, 1423-1435
Abstract:
In order to obtain a two-tailed confidence interval for the difference between two proportions (independent samples), the current literature on the subject has proposed a great number of asymptotic methods. This paper assesses 80 classical asymptotic methods (including the best proposals made in the literature) and concludes that (1) the best solution consists of adding 0.5 to all of the data and inverting the test based on the arcsine transformation; (2) a solution which is a little worse than the previous one (but much easier and even better when both samples are balanced) is a modification of the adjusted Wald method proposed by Agresti and Caffo (usually adding to all of the data and then applying the classical Wald CI); (3) surprisingly, the classical score method is among the worst solutions, since it provides excessively liberal results.
Date: 2012
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/02664763.2011.650686 (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:japsta:v:39:y:2012:i:7:p:1423-1435
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20
DOI: 10.1080/02664763.2011.650686
Access Statistics for this article
Journal of Applied Statistics is currently edited by Robert Aykroyd
More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().