Mixed models in cerebral ischemia study
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Acta scientiarum. Technology (Online) |
Texto Completo: | http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/28314 |
Resumo: | The data modeling from longitudinal studies stands out in the current scientific scenario, especially in the areas of health and biological sciences, which induces a correlation between measurements for the same observed unit. Thus, the modeling of the intra-individual dependency is required through the choice of a covariance structure that is able to receive and accommodate the sample variability. However, the lack of methodology for correlated data analysis may result in an increased occurrence of type I or type II errors and underestimate/overestimate the standard errors of the model estimates. In the present study, a Gaussian mixed model was adopted for the variable response latency of an experiment investigating the memory deficits in animals subjected to cerebral ischemia when treated with fish oil (FO). The model parameters estimation was based on maximum likelihood methods. Based on the restricted likelihood ratio test and information criteria, the autoregressive covariance matrix was adopted for errors. The diagnostic analyses for the model were satisfactory, since basic assumptions and results obtained corroborate with biological evidence; that is, the effectiveness of the FO treatment to alleviate the cognitive effects caused by cerebral ischemia was found. |
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Acta scientiarum. Technology (Online) |
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Mixed models in cerebral ischemia studylongitudinal datarandom effectcovariance structurelatencyfish oilEstatísticaThe data modeling from longitudinal studies stands out in the current scientific scenario, especially in the areas of health and biological sciences, which induces a correlation between measurements for the same observed unit. Thus, the modeling of the intra-individual dependency is required through the choice of a covariance structure that is able to receive and accommodate the sample variability. However, the lack of methodology for correlated data analysis may result in an increased occurrence of type I or type II errors and underestimate/overestimate the standard errors of the model estimates. In the present study, a Gaussian mixed model was adopted for the variable response latency of an experiment investigating the memory deficits in animals subjected to cerebral ischemia when treated with fish oil (FO). The model parameters estimation was based on maximum likelihood methods. Based on the restricted likelihood ratio test and information criteria, the autoregressive covariance matrix was adopted for errors. The diagnostic analyses for the model were satisfactory, since basic assumptions and results obtained corroborate with biological evidence; that is, the effectiveness of the FO treatment to alleviate the cognitive effects caused by cerebral ischemia was found. Universidade Estadual De Maringá2016-06-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/2831410.4025/actascitechnol.v38i3.28314Acta Scientiarum. Technology; Vol 38 No 3 (2016); 345-352Acta Scientiarum. Technology; v. 38 n. 3 (2016); 345-3521806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/28314/pdfCopyright (c) 2016 Acta Scientiarum. Technologyinfo:eu-repo/semantics/openAccessRibeiro, Matheus Henrique Dal MolinMilani, HumbertoPrevidelli, Isolde2016-07-12T15:33:47Zoai:periodicos.uem.br/ojs:article/28314Revistahttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/indexPUBhttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2016-07-12T15:33:47Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false |
dc.title.none.fl_str_mv |
Mixed models in cerebral ischemia study |
title |
Mixed models in cerebral ischemia study |
spellingShingle |
Mixed models in cerebral ischemia study Ribeiro, Matheus Henrique Dal Molin longitudinal data random effect covariance structure latency fish oil Estatística |
title_short |
Mixed models in cerebral ischemia study |
title_full |
Mixed models in cerebral ischemia study |
title_fullStr |
Mixed models in cerebral ischemia study |
title_full_unstemmed |
Mixed models in cerebral ischemia study |
title_sort |
Mixed models in cerebral ischemia study |
author |
Ribeiro, Matheus Henrique Dal Molin |
author_facet |
Ribeiro, Matheus Henrique Dal Molin Milani, Humberto Previdelli, Isolde |
author_role |
author |
author2 |
Milani, Humberto Previdelli, Isolde |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Ribeiro, Matheus Henrique Dal Molin Milani, Humberto Previdelli, Isolde |
dc.subject.por.fl_str_mv |
longitudinal data random effect covariance structure latency fish oil Estatística |
topic |
longitudinal data random effect covariance structure latency fish oil Estatística |
description |
The data modeling from longitudinal studies stands out in the current scientific scenario, especially in the areas of health and biological sciences, which induces a correlation between measurements for the same observed unit. Thus, the modeling of the intra-individual dependency is required through the choice of a covariance structure that is able to receive and accommodate the sample variability. However, the lack of methodology for correlated data analysis may result in an increased occurrence of type I or type II errors and underestimate/overestimate the standard errors of the model estimates. In the present study, a Gaussian mixed model was adopted for the variable response latency of an experiment investigating the memory deficits in animals subjected to cerebral ischemia when treated with fish oil (FO). The model parameters estimation was based on maximum likelihood methods. Based on the restricted likelihood ratio test and information criteria, the autoregressive covariance matrix was adopted for errors. The diagnostic analyses for the model were satisfactory, since basic assumptions and results obtained corroborate with biological evidence; that is, the effectiveness of the FO treatment to alleviate the cognitive effects caused by cerebral ischemia was found. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-06-22 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/28314 10.4025/actascitechnol.v38i3.28314 |
url |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/28314 |
identifier_str_mv |
10.4025/actascitechnol.v38i3.28314 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/28314/pdf |
dc.rights.driver.fl_str_mv |
Copyright (c) 2016 Acta Scientiarum. Technology info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2016 Acta Scientiarum. Technology |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
dc.source.none.fl_str_mv |
Acta Scientiarum. Technology; Vol 38 No 3 (2016); 345-352 Acta Scientiarum. Technology; v. 38 n. 3 (2016); 345-352 1806-2563 1807-8664 reponame:Acta scientiarum. Technology (Online) instname:Universidade Estadual de Maringá (UEM) instacron:UEM |
instname_str |
Universidade Estadual de Maringá (UEM) |
instacron_str |
UEM |
institution |
UEM |
reponame_str |
Acta scientiarum. Technology (Online) |
collection |
Acta scientiarum. Technology (Online) |
repository.name.fl_str_mv |
Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM) |
repository.mail.fl_str_mv |
||actatech@uem.br |
_version_ |
1799315335885619200 |