Separation phenomena logistic regression

Detalhes bibliográficos
Autor(a) principal: Barreto, Ikaro Daniel de Carvalho
Data de Publicação: 2014
Outros Autores: Russo, Suzana Leitão, Brasil, Gutemberg Hespanha, Simon, Vitor Hugo
Tipo de documento: Artigo
Idioma: por
Título da fonte: Revista GEINTEC: Gestão. Inovação e Tecnologias
Texto Completo: http://www.revistageintec.net/index.php/revista/article/view/378
Resumo: This paper proposes an application of concepts about the maximum likelihood estimation of the binomial logistic regression model to the separation phenomena. It generates bias in the estimation and provides different interpretations of the estimates on the different statistical tests (Wald, Likelihood Ratio and Score) and provides different estimates on the different iterative methods (Newton-Raphson and Fisher Score). It also presents an example that demonstrates the direct implications for the validation of the model and validation of variables, the implications for estimates of odds ratios and confidence intervals, generated from the Wald statistics. Furthermore, we present, briefly, the Firth correction to circumvent the phenomena of separation.
id AESPI-1_0b74bf1f0b9f7f7af77f01357d0a35f8
oai_identifier_str oai:ojs.pkp.sfu.ca:article/378
network_acronym_str AESPI-1
network_name_str Revista GEINTEC: Gestão. Inovação e Tecnologias
spelling Separation phenomena logistic regressionThis paper proposes an application of concepts about the maximum likelihood estimation of the binomial logistic regression model to the separation phenomena. It generates bias in the estimation and provides different interpretations of the estimates on the different statistical tests (Wald, Likelihood Ratio and Score) and provides different estimates on the different iterative methods (Newton-Raphson and Fisher Score). It also presents an example that demonstrates the direct implications for the validation of the model and validation of variables, the implications for estimates of odds ratios and confidence intervals, generated from the Wald statistics. Furthermore, we present, briefly, the Firth correction to circumvent the phenomena of separation.API - Associação Acadêmica de Propriedade IntelectualBarreto, Ikaro Daniel de CarvalhoRusso, Suzana LeitãoBrasil, Gutemberg HespanhaSimon, Vitor Hugo2014-03-17info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionNÃO ESTÁ ATIVAapplication/pdfhttp://www.revistageintec.net/index.php/revista/article/view/37810.7198/geintec.v4i1.378Revista GEINTEC - Gestão, Inovação e Tecnologias; v. 4, n. 1 (2014); 716-7282237-0722reponame:Revista GEINTEC: Gestão. Inovação e Tecnologiasinstname:Ensino Superior do Piauí (AESPI)instacron:AESPIporhttp://www.revistageintec.net/index.php/revista/article/view/378/394info:eu-repo/semantics/openAccess2019-10-06T00:04:47Zoai:ojs.pkp.sfu.ca:article/378Revistahttp://www.revistageintec.net/index.php/revista/oai2237-07222237-0722opendoar:null2020-06-25 22:43:05.599Revista GEINTEC: Gestão. Inovação e Tecnologias - Ensino Superior do Piauí (AESPI)true
dc.title.none.fl_str_mv Separation phenomena logistic regression
title Separation phenomena logistic regression
spellingShingle Separation phenomena logistic regression
Barreto, Ikaro Daniel de Carvalho
title_short Separation phenomena logistic regression
title_full Separation phenomena logistic regression
title_fullStr Separation phenomena logistic regression
title_full_unstemmed Separation phenomena logistic regression
title_sort Separation phenomena logistic regression
author Barreto, Ikaro Daniel de Carvalho
author_facet Barreto, Ikaro Daniel de Carvalho
Russo, Suzana Leitão
Brasil, Gutemberg Hespanha
Simon, Vitor Hugo
author_role author
author2 Russo, Suzana Leitão
Brasil, Gutemberg Hespanha
Simon, Vitor Hugo
author2_role author
author
author
dc.contributor.none.fl_str_mv
dc.contributor.author.fl_str_mv Barreto, Ikaro Daniel de Carvalho
Russo, Suzana Leitão
Brasil, Gutemberg Hespanha
Simon, Vitor Hugo
dc.subject.none.fl_str_mv
dc.description.none.fl_txt_mv This paper proposes an application of concepts about the maximum likelihood estimation of the binomial logistic regression model to the separation phenomena. It generates bias in the estimation and provides different interpretations of the estimates on the different statistical tests (Wald, Likelihood Ratio and Score) and provides different estimates on the different iterative methods (Newton-Raphson and Fisher Score). It also presents an example that demonstrates the direct implications for the validation of the model and validation of variables, the implications for estimates of odds ratios and confidence intervals, generated from the Wald statistics. Furthermore, we present, briefly, the Firth correction to circumvent the phenomena of separation.
description This paper proposes an application of concepts about the maximum likelihood estimation of the binomial logistic regression model to the separation phenomena. It generates bias in the estimation and provides different interpretations of the estimates on the different statistical tests (Wald, Likelihood Ratio and Score) and provides different estimates on the different iterative methods (Newton-Raphson and Fisher Score). It also presents an example that demonstrates the direct implications for the validation of the model and validation of variables, the implications for estimates of odds ratios and confidence intervals, generated from the Wald statistics. Furthermore, we present, briefly, the Firth correction to circumvent the phenomena of separation.
publishDate 2014
dc.date.none.fl_str_mv 2014-03-17
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
NÃO ESTÁ ATIVA
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.revistageintec.net/index.php/revista/article/view/378
10.7198/geintec.v4i1.378
url http://www.revistageintec.net/index.php/revista/article/view/378
identifier_str_mv 10.7198/geintec.v4i1.378
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv http://www.revistageintec.net/index.php/revista/article/view/378/394
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv API - Associação Acadêmica de Propriedade Intelectual
publisher.none.fl_str_mv API - Associação Acadêmica de Propriedade Intelectual
dc.source.none.fl_str_mv Revista GEINTEC - Gestão, Inovação e Tecnologias; v. 4, n. 1 (2014); 716-728
2237-0722
reponame:Revista GEINTEC: Gestão. Inovação e Tecnologias
instname:Ensino Superior do Piauí (AESPI)
instacron:AESPI
reponame_str Revista GEINTEC: Gestão. Inovação e Tecnologias
collection Revista GEINTEC: Gestão. Inovação e Tecnologias
instname_str Ensino Superior do Piauí (AESPI)
instacron_str AESPI
institution AESPI
repository.name.fl_str_mv Revista GEINTEC: Gestão. Inovação e Tecnologias - Ensino Superior do Piauí (AESPI)
repository.mail.fl_str_mv
_version_ 1674121144935907328