Publicação
Interval Estimators for a Binomial Proportion: Comparison of Twenty Methods
| Resumo: | In applied statistics it is often necessary to obtain an interval estimate for an unknown proportion (p) based on binomial sampling. This topic is considered in almost every introductory course. However, the usual approximation is known to be poor when the true p is close to zero or to one. To identify alternative procedures with better properties twenty non-iterative methods for computing a (central) two-sided interval estimate for p were selected and compared in terms of coverage probability and expected length. From this study a clear classification of those methods has emerged. An important conclusion is that the interval based on asymptotic normality, but after the arcsine transformation and a continuity correction, and the Add 4 method of Agresti and Coull (1998) yield very reliable results, the choice between the two depending on the desired degree of conservativeness. |
|---|---|
| Autores principais: | Pires , Ana M. |
| Outros Autores: | Amado , Conceição |
| Assunto: | confidence interval binomial distribution proportion test normal approximation arcsine transformation continuity correction bootstrap HPD credibility intervals |
| Ano: | 2008 |
| País: | portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | unknown |
| Instituição associada: | Instituto Nacional de Estatística |
| Idioma: | inglês |
| Origem: | REVSTAT-Statistical Journal |
| _version_ | 1869054297011912704 |
|---|---|
| author | Pires , Ana M. |
| author2 | Amado , Conceição |
| author2_role | author |
| author_facet | Pires , Ana M. Amado , Conceição |
| author_role | author |
| country_str | portugal |
| creators_json_txt | [{\"Person.name\":\"Pires , Ana M.\"},{\"Person.name\":\"Amado , Conceição\"}] |
| datacite.creators.creator.creatorName.fl_str_mv | Pires , Ana M. Amado , Conceição |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | confidence interval binomial distribution proportion test normal approximation arcsine transformation continuity correction bootstrap HPD credibility intervals |
| datacite.titles.title.fl_str_mv | Interval Estimators for a Binomial Proportion: Comparison of Twenty Methods |
| dc.creator.none.fl_str_mv | Pires , Ana M. Amado , Conceição |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://doi.org/10.57805/revstat.v6i2.63 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Statistics Portugal |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.source.none.fl_str_mv | REVSTAT-Statistical Journal; Vol. 6 No. 2 (2008): REVSTAT-Statistical Journal; 165–197 REVSTAT; Vol. 6 N.º 2 (2008): REVSTAT-Statistical Journal; 165–197 2183-0371 1645-6726 |
| dc.subject.none.fl_str_mv | confidence interval binomial distribution proportion test normal approximation arcsine transformation continuity correction bootstrap HPD credibility intervals |
| dc.title.fl_str_mv | Interval Estimators for a Binomial Proportion: Comparison of Twenty Methods |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | In applied statistics it is often necessary to obtain an interval estimate for an unknown proportion (p) based on binomial sampling. This topic is considered in almost every introductory course. However, the usual approximation is known to be poor when the true p is close to zero or to one. To identify alternative procedures with better properties twenty non-iterative methods for computing a (central) two-sided interval estimate for p were selected and compared in terms of coverage probability and expected length. From this study a clear classification of those methods has emerged. An important conclusion is that the interval based on asymptotic normality, but after the arcsine transformation and a continuity correction, and the Add 4 method of Agresti and Coull (1998) yield very reliable results, the choice between the two depending on the desired degree of conservativeness. |
| dirty | 0 |
| eu_rights_str_mv | unknown |
| format | article |
| id | revstat_9624165cc440fd2be2ca2fd6fa87f2ec |
| identifier.doi.fl_str_mv | https://doi.org/10.57805/revstat.v6i2.63 |
| inst_facet_str | urn:organizationAcronym:revstat-statistical journal{{{_:::_}}}Instituto Nacional de Estatística |
| instacron_str | REVSTAT-Statistical Journal |
| institution | Instituto Nacional de Estatística |
| instname_str | Instituto Nacional de Estatística |
| language | eng |
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| network_name_str | REVSTAT-Statistical Journal |
| oai_identifier_str | oai:revstat:article/63 |
| organization_str_mv | urn:organizationAcronym:revstat-statistical journal |
| person_str_mv | Pires , Ana M. Amado , Conceição |
| publishDate | 2008 |
| publisher.none.fl_str_mv | Statistics Portugal |
| repo_facet_str | urn:repositoryAcronym:revstat{{{_:::_}}}REVSTAT-Statistical Journal |
| reponame_str | REVSTAT-Statistical Journal |
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| spelling | en-USInterval Estimators for a Binomial Proportion: Comparison of Twenty MethodsPires , Ana M.Amado , Conceiçãoconfidence intervalbinomial distributionproportion testnormal approximationarcsine transformationcontinuity correctionbootstrapHPD credibility intervalsCopyright (c) 2008 REVSTAT-Statistical Journalhttp://purl.org/coar/access_right/c_abf2https://creativecommons.org/licenses/by/4.0https://doi.org/10.57805/revstat.v6i2.63DOIoai:revstat:article/63OAIhttps://revstat.ine.pt/index.php/REVSTAT/article/view/63URLhttps://doi.org/10.57805/revstat.v6i2.63DOIhttps://revstat.ine.pt/index.php/REVSTAT/article/view/63/67URLHasVersion2008-06-24T00:00:00Zen-USIn applied statistics it is often necessary to obtain an interval estimate for an unknown proportion (p) based on binomial sampling. This topic is considered in almost every introductory course. However, the usual approximation is known to be poor when the true p is close to zero or to one. To identify alternative procedures with better properties twenty non-iterative methods for computing a (central) two-sided interval estimate for p were selected and compared in terms of coverage probability and expected length. From this study a clear classification of those methods has emerged. An important conclusion is that the interval based on asymptotic normality, but after the arcsine transformation and a continuity correction, and the Add 4 method of Agresti and Coull (1998) yield very reliable results, the choice between the two depending on the desired degree of conservativeness.Statistics Portugalapplication/pdfen-USREVSTAT-Statistical Journal; Vol. 6 No. 2 (2008): REVSTAT-Statistical Journal; 165–197pt-PTREVSTAT; Vol. 6 N.º 2 (2008): REVSTAT-Statistical Journal; 165–1972183-03711645-6726engjournal articlehttp://purl.org/coar/resource_type/c_6501literatureVoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85 |
| spellingShingle | Interval Estimators for a Binomial Proportion: Comparison of Twenty Methods Pires , Ana M. confidence interval binomial distribution proportion test normal approximation arcsine transformation continuity correction bootstrap HPD credibility intervals |
| status | SINGLETON |
| status_str | VoR |
| subject.fl_str_mv | confidence interval binomial distribution proportion test normal approximation arcsine transformation continuity correction bootstrap HPD credibility intervals |
| title | Interval Estimators for a Binomial Proportion: Comparison of Twenty Methods |
| title_full | Interval Estimators for a Binomial Proportion: Comparison of Twenty Methods |
| title_fullStr | Interval Estimators for a Binomial Proportion: Comparison of Twenty Methods |
| title_full_unstemmed | Interval Estimators for a Binomial Proportion: Comparison of Twenty Methods |
| title_short | Interval Estimators for a Binomial Proportion: Comparison of Twenty Methods |
| title_sort | Interval Estimators for a Binomial Proportion: Comparison of Twenty Methods |
| topic | confidence interval binomial distribution proportion test normal approximation arcsine transformation continuity correction bootstrap HPD credibility intervals |
| topic_facet | confidence interval binomial distribution proportion test normal approximation arcsine transformation continuity correction bootstrap HPD credibility intervals |
| url | https://doi.org/10.57805/revstat.v6i2.63 |
| visible | 1 |