A Novel Statistical Analysis of Cnidocysts in Acontiarian Sea Anemones (Cnidaria, Actiniaria) Using Generalized Linear Models with Gamma Errors

Autores
Acuña, Fabian Horacio; Ricci, Lila; Excoffon, Adriana Carmen; Zamponi, Mauricio Oscar
Año de publicación
2004
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Comparative studies on cnidocysts, involving adequate statistical treatment, are very scarce. Classical statistical tests are frequently used assuming normal frequency distributions of capsule lengths, but many distributions are non-normal in acontiarian sea anemones. A traditional choice in these situations are non-parametric tests, although they are not as powerful as parametric tests. An extension of classical methods was developed by some authors; these models, called Generalized Linear Models (GLM), can be used under certain conditions with non-normal data. In view of the properties of our data, that are positive, skewed and with constant coefficient of variation, a Generalized Linear Model with gamma distribution and inverse link function was chosen to analyse the cnidae of acontia from the species Haliplanella lineata, Tricnidactis errans and Anthothoe chilensis. Graphical analysis of residuals showed that these assumptions were reasonable. This method allowed us to avoid transformation of dataset and controversial cases in the limit of significance level. For this task, appropriate subroutines in GLIM language were written. In all cases highly significant differences were found between the specimens considered for every species and nematocyst type (b-rhabdoids, p-rhabdoids B1b and p-rhabdoids B2a).
Fil: Acuña, Fabian Horacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; Argentina
Fil: Ricci, Lila. Universidad Nacional de Mar del Plata; Argentina
Fil: Excoffon, Adriana Carmen. Universidad Nacional de Mar del Plata; Argentina
Fil: Zamponi, Mauricio Oscar. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
CNIDAE LENGTH
STATISTICS
GAMMA DISTRIBUTION
ACONTIARIA
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/155578
Acceder
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network_name_str CONICET Digital (CONICET)
spelling A Novel Statistical Analysis of Cnidocysts in Acontiarian Sea Anemones (Cnidaria, Actiniaria) Using Generalized Linear Models with Gamma ErrorsAcuña, Fabian HoracioRicci, LilaExcoffon, Adriana CarmenZamponi, Mauricio OscarCNIDAE LENGTHSTATISTICSGAMMA DISTRIBUTIONACONTIARIAhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Comparative studies on cnidocysts, involving adequate statistical treatment, are very scarce. Classical statistical tests are frequently used assuming normal frequency distributions of capsule lengths, but many distributions are non-normal in acontiarian sea anemones. A traditional choice in these situations are non-parametric tests, although they are not as powerful as parametric tests. An extension of classical methods was developed by some authors; these models, called Generalized Linear Models (GLM), can be used under certain conditions with non-normal data. In view of the properties of our data, that are positive, skewed and with constant coefficient of variation, a Generalized Linear Model with gamma distribution and inverse link function was chosen to analyse the cnidae of acontia from the species Haliplanella lineata, Tricnidactis errans and Anthothoe chilensis. Graphical analysis of residuals showed that these assumptions were reasonable. This method allowed us to avoid transformation of dataset and controversial cases in the limit of significance level. For this task, appropriate subroutines in GLIM language were written. In all cases highly significant differences were found between the specimens considered for every species and nematocyst type (b-rhabdoids, p-rhabdoids B1b and p-rhabdoids B2a).Fil: Acuña, Fabian Horacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Ricci, Lila. Universidad Nacional de Mar del Plata; ArgentinaFil: Excoffon, Adriana Carmen. Universidad Nacional de Mar del Plata; ArgentinaFil: Zamponi, Mauricio Oscar. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaElsevier Gmbh2004-11-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/155578Acuña, Fabian Horacio; Ricci, Lila; Excoffon, Adriana Carmen; Zamponi, Mauricio Oscar; A Novel Statistical Analysis of Cnidocysts in Acontiarian Sea Anemones (Cnidaria, Actiniaria) Using Generalized Linear Models with Gamma Errors; Elsevier Gmbh; Zoologischer Anzeiger; 243; 1-2; 8-11-2004; 47-520044-5231CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0044523104000075?via%3Dihubinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.jcz.2004.06.002info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:41:57Zoai:ri.conicet.gov.ar:11336/155578instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:41:58.144CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A Novel Statistical Analysis of Cnidocysts in Acontiarian Sea Anemones (Cnidaria, Actiniaria) Using Generalized Linear Models with Gamma Errors
title A Novel Statistical Analysis of Cnidocysts in Acontiarian Sea Anemones (Cnidaria, Actiniaria) Using Generalized Linear Models with Gamma Errors
spellingShingle A Novel Statistical Analysis of Cnidocysts in Acontiarian Sea Anemones (Cnidaria, Actiniaria) Using Generalized Linear Models with Gamma Errors
Acuña, Fabian Horacio
CNIDAE LENGTH
STATISTICS
GAMMA DISTRIBUTION
ACONTIARIA
title_short A Novel Statistical Analysis of Cnidocysts in Acontiarian Sea Anemones (Cnidaria, Actiniaria) Using Generalized Linear Models with Gamma Errors
title_full A Novel Statistical Analysis of Cnidocysts in Acontiarian Sea Anemones (Cnidaria, Actiniaria) Using Generalized Linear Models with Gamma Errors
title_fullStr A Novel Statistical Analysis of Cnidocysts in Acontiarian Sea Anemones (Cnidaria, Actiniaria) Using Generalized Linear Models with Gamma Errors
title_full_unstemmed A Novel Statistical Analysis of Cnidocysts in Acontiarian Sea Anemones (Cnidaria, Actiniaria) Using Generalized Linear Models with Gamma Errors
title_sort A Novel Statistical Analysis of Cnidocysts in Acontiarian Sea Anemones (Cnidaria, Actiniaria) Using Generalized Linear Models with Gamma Errors
dc.creator.none.fl_str_mv Acuña, Fabian Horacio
Ricci, Lila
Excoffon, Adriana Carmen
Zamponi, Mauricio Oscar
author Acuña, Fabian Horacio
author_facet Acuña, Fabian Horacio
Ricci, Lila
Excoffon, Adriana Carmen
Zamponi, Mauricio Oscar
author_role author
author2 Ricci, Lila
Excoffon, Adriana Carmen
Zamponi, Mauricio Oscar
author2_role author
author
author
dc.subject.none.fl_str_mv CNIDAE LENGTH
STATISTICS
GAMMA DISTRIBUTION
ACONTIARIA
topic CNIDAE LENGTH
STATISTICS
GAMMA DISTRIBUTION
ACONTIARIA
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Comparative studies on cnidocysts, involving adequate statistical treatment, are very scarce. Classical statistical tests are frequently used assuming normal frequency distributions of capsule lengths, but many distributions are non-normal in acontiarian sea anemones. A traditional choice in these situations are non-parametric tests, although they are not as powerful as parametric tests. An extension of classical methods was developed by some authors; these models, called Generalized Linear Models (GLM), can be used under certain conditions with non-normal data. In view of the properties of our data, that are positive, skewed and with constant coefficient of variation, a Generalized Linear Model with gamma distribution and inverse link function was chosen to analyse the cnidae of acontia from the species Haliplanella lineata, Tricnidactis errans and Anthothoe chilensis. Graphical analysis of residuals showed that these assumptions were reasonable. This method allowed us to avoid transformation of dataset and controversial cases in the limit of significance level. For this task, appropriate subroutines in GLIM language were written. In all cases highly significant differences were found between the specimens considered for every species and nematocyst type (b-rhabdoids, p-rhabdoids B1b and p-rhabdoids B2a).
Fil: Acuña, Fabian Horacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; Argentina
Fil: Ricci, Lila. Universidad Nacional de Mar del Plata; Argentina
Fil: Excoffon, Adriana Carmen. Universidad Nacional de Mar del Plata; Argentina
Fil: Zamponi, Mauricio Oscar. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Comparative studies on cnidocysts, involving adequate statistical treatment, are very scarce. Classical statistical tests are frequently used assuming normal frequency distributions of capsule lengths, but many distributions are non-normal in acontiarian sea anemones. A traditional choice in these situations are non-parametric tests, although they are not as powerful as parametric tests. An extension of classical methods was developed by some authors; these models, called Generalized Linear Models (GLM), can be used under certain conditions with non-normal data. In view of the properties of our data, that are positive, skewed and with constant coefficient of variation, a Generalized Linear Model with gamma distribution and inverse link function was chosen to analyse the cnidae of acontia from the species Haliplanella lineata, Tricnidactis errans and Anthothoe chilensis. Graphical analysis of residuals showed that these assumptions were reasonable. This method allowed us to avoid transformation of dataset and controversial cases in the limit of significance level. For this task, appropriate subroutines in GLIM language were written. In all cases highly significant differences were found between the specimens considered for every species and nematocyst type (b-rhabdoids, p-rhabdoids B1b and p-rhabdoids B2a).
publishDate 2004
dc.date.none.fl_str_mv 2004-11-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/155578
Acuña, Fabian Horacio; Ricci, Lila; Excoffon, Adriana Carmen; Zamponi, Mauricio Oscar; A Novel Statistical Analysis of Cnidocysts in Acontiarian Sea Anemones (Cnidaria, Actiniaria) Using Generalized Linear Models with Gamma Errors; Elsevier Gmbh; Zoologischer Anzeiger; 243; 1-2; 8-11-2004; 47-52
0044-5231
CONICET Digital
CONICET
url http://hdl.handle.net/11336/155578
identifier_str_mv Acuña, Fabian Horacio; Ricci, Lila; Excoffon, Adriana Carmen; Zamponi, Mauricio Oscar; A Novel Statistical Analysis of Cnidocysts in Acontiarian Sea Anemones (Cnidaria, Actiniaria) Using Generalized Linear Models with Gamma Errors; Elsevier Gmbh; Zoologischer Anzeiger; 243; 1-2; 8-11-2004; 47-52
0044-5231
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0044523104000075?via%3Dihub
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jcz.2004.06.002
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Gmbh
publisher.none.fl_str_mv Elsevier Gmbh
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.22299

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