A comparison of approximate confidence interval methods for the difference between two independent binomial proportions

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dc.contributor.authorNel, M.
dc.contributor.authorSchall, R.
dc.contributor.authorNel, D.G.
dc.contributor.authorJoubert, G.
dc.contributor.authorNel, M.
dc.contributor.authorSchall, R.
dc.contributor.authorNel, D.G.
dc.contributor.authorJoubert, G.
dc.date.accessioned2011-05-15T16:02:32Z
dc.date.accessioned2011-05-15T16:02:32Z
dc.date.available2011-05-15T16:02:32Z
dc.date.available2011-05-15T16:02:32Z
dc.date.issued2002
dc.date.issued2002
dc.descriptionConventional methods to determine confidence intervals for the difference between two independent binomial proportions p1 and p2 are prone to violations of the definition interval [-1; 1] for p1-p2 and may have very poor coverage properties. In this paper several less known methods are described. A simulation study was done to compare the different confidence interval methods with respect to length, coverage, zero width interval and violation of the definition interval. The best methods were found to be Mee's and Miettinen and Nurminen's method. These methods, however, are computer intensive. The Jeffreys-Perks and Score interval methods seem to be the best of the more easily calculable methods to use in most practical situations.
dc.description.abstractConventional methods to determine confidence intervals for the difference between two independent binomial proportions p1 and p2 are prone to violations of the definition interval [-1; 1] for p1-p2 and may have very poor coverage properties. In this paper several less known methods are described. A simulation study was done to compare the different confidence interval methods with respect to length, coverage, zero width interval and violation of the definition interval. The best methods were found to be Mee's and Miettinen and Nurminen's method. These methods, however, are computer intensive. The Jeffreys-Perks and Score interval methods seem to be the best of the more easily calculable methods to use in most practical situations.
dc.description.abstractConventional methods to determine confidence intervals for the difference between two independent binomial proportions p1 and p2 are prone to violations of the definition interval [-1; 1] for p1-p2 and may have very poor coverage properties. In this paper several less known methods are described. A simulation study was done to compare the different confidence interval methods with respect to length, coverage, zero width interval and violation of the definition interval. The best methods were found to be Mee's and Miettinen and Nurminen's method. These methods, however, are computer intensive. The Jeffreys-Perks and Score interval methods seem to be the best of the more easily calculable methods to use in most practical situations.
dc.description.versionArticle
dc.description.versionArticle
dc.identifier.citationSouth African Statistical Journal
dc.identifier.citation36
dc.identifier.citation1
dc.identifier.citationSouth African Statistical Journal
dc.identifier.citation36
dc.identifier.citation1
dc.identifier.issn0038271X
dc.identifier.issn0038271X
dc.identifier.urihttp://hdl.handle.net/10019.1/12516
dc.identifier.urihttp://hdl.handle.net/10019.1/12516
dc.titleA comparison of approximate confidence interval methods for the difference between two independent binomial proportions
dc.titleA comparison of approximate confidence interval methods for the difference between two independent binomial proportions
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