102013-03-08 10:17:37localhostconverted to 1.6 markup92012-06-25 14:01:53PeterWatson82010-08-27 09:21:23PeterWatson72010-08-26 15:50:41PeterWatson62010-08-26 15:49:57PeterWatson52010-08-26 15:28:28PeterWatson42010-08-26 15:28:00PeterWatson32010-08-26 14:14:38PeterWatson22010-08-26 09:11:30PeterWatson12010-08-26 09:11:21PeterWatson

McNemar's test is commonly used to test whether two correlated proportions differ. Unfortunately this test does not tprovide a confidence interval for the difference in proportions. The classical Wald statistic which is used for constructing confidence intervals for proportions produces too narrow a confidence interval when the difference in proportions is close to zero or one (Newcombe (1998)). Newcombe, instead, suggests using a modification of Wilson's (1927) method based on a single proportion. Agresti & Kin (2005) also find Wilson's method produces good coverage and also suggest an improved confidence interval may be obtained by a simple modification of the Wald statistic. These are all included in this EXCEL spreadsheet. Some R code for the Agresti-Min approach above is also available References Agresti A and Min Y (2005) Simple improved confidence intervals for comparing matched proportions. Statistics in Medicine 24(5) 729-740. Newcombe RG (1998) Improved confidence intervals for the difference between binomial proportions based on paired data. Statistics in Medicine 17 2635-2650. Lee S & Lee S-C (2007) An improved confidence interval for the population proportion in a double sampling scheme subject to false-positive misclassification, Journal of the Korean Statistical Society 36 275–284. (reference for agrestic-oull method used in above spreadsheet).