Sample size for evaluation the of multicollinearity degree in productive traits of rye

Bibliographic Details
Main Author: Neu, Ismael Mario Márcio
Publication Date: 2022
Other Authors: Cargnelutti Filho, Alberto, de Bem, Cláudia Marques, Kleinpaul, Jéssica Andiara, Bandeira, Cirineu Tolfo
Format: Article
Language: por
Source: Revista Ciência e Natura (Online)
Download full: https://periodicos.ufsm.br/cienciaenatura/article/view/41667
Summary: The objectives of this work were to determine the sample size (number of plants) necessary to estimate the indicators of the of multicollinearity degree - condition number (CN), determinant of the correlation matrix (DET), and variance inflation factor (VIF) - in productive traits of rye and to verify the variability of the sample size between the indicators. Five and three uniformity trials were conducted with the cultivars BRS Progresso and Temprano, respectively, and seven productive traits were evaluated in 780 plants. Twenty-one cases were obtained from seven traits, combined five to five. In each case, 197 sample sizes were planned (20, 25, 30, ..., 1,000 plants) and in each size 2,000 resampling were performed, with replacement. For each resample the CN, DET and FIV were determined and the average among 2,000 estimates of each indicator of the multicollinearity degree was calculated. Then, for each case and indicator, the sample size was determined through three models: models of maximum modified curvature, segmented linear with plateau response, and segmented quadratic with plateau response. There was superiority the quadratic model segmented with plateau in adjusting the degree of multicollinearity according to the sample size for all indicators. There is a need greater sample size to detect multicollinearity when diagnosed by DET and for sizes larger than 101, 258 and 102 plants when diagnosing for the number of conditions, determinant and inflation factor performed, respectively.
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spelling Sample size for evaluation the of multicollinearity degree in productive traits of ryeTamanho de amostra para avaliação do grau de multicolinearidade em caracteres produtivos de centeioSecale cereale LSampling designCorrelationMultivariate analysisSecale cereale LDimensionamento amostralCorrelaçãoAnálise multivariadaThe objectives of this work were to determine the sample size (number of plants) necessary to estimate the indicators of the of multicollinearity degree - condition number (CN), determinant of the correlation matrix (DET), and variance inflation factor (VIF) - in productive traits of rye and to verify the variability of the sample size between the indicators. Five and three uniformity trials were conducted with the cultivars BRS Progresso and Temprano, respectively, and seven productive traits were evaluated in 780 plants. Twenty-one cases were obtained from seven traits, combined five to five. In each case, 197 sample sizes were planned (20, 25, 30, ..., 1,000 plants) and in each size 2,000 resampling were performed, with replacement. For each resample the CN, DET and FIV were determined and the average among 2,000 estimates of each indicator of the multicollinearity degree was calculated. Then, for each case and indicator, the sample size was determined through three models: models of maximum modified curvature, segmented linear with plateau response, and segmented quadratic with plateau response. There was superiority the quadratic model segmented with plateau in adjusting the degree of multicollinearity according to the sample size for all indicators. There is a need greater sample size to detect multicollinearity when diagnosed by DET and for sizes larger than 101, 258 and 102 plants when diagnosing for the number of conditions, determinant and inflation factor performed, respectively.Os objetivos deste trabalho foram determinar o tamanho de amostra (número de plantas) necessário para a estimação dos indicadores do grau de multicolinearidade - número de condição (NC), determinante da matriz de correlação (DET) e fator de inflação da variância (FIV) - em caracteres produtivos de centeio e verificar a variabilidade do tamanho de amostra entre os indicadores. Foram conduzidos cinco e três ensaios de uniformidade (cultivares BRS Progresso e Temprano, respectivamente) e avaliados sete caracteres produtivos em 780 plantas. Vinte e um casos foram obtidos a partir de sete caracteres, combinados cinco a cinco. Para cada caso, foram planejados 197 tamanhos de amostra (20, 25, 30, ..., 1.000 plantas) e para cada tamanho foram realizadas 2.000 reamostragens, com reposição. Para cada reamostra foram determinados o NC, DET e FIV e calculada a média das 2.000 estimativas de cada indicador do grau de multicolinearidade. Após, foi determinado o tamanho de amostra, por meio de: máxima curvatura modificado e modelos linear e quadrático segmentado com resposta platô. Houve superioridade do modelo quadrático segmentado com platô no ajuste do grau de multicolinearidade em função do tamanho de amostra para todos os indicadores. Há a necessidade de maior tamanho de amostra para a detecção da multicolinearidade quando o diagnóstico for realizado pelo DET e de tamanhos de amostra superiores a 101, 258 e 102 plantas quando o diagnóstico for realizado pelo número de condição, determinante e fator de inflação da variância, respectivamente.Universidade Federal de Santa Maria2022-01-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/htmlhttps://periodicos.ufsm.br/cienciaenatura/article/view/4166710.5902/2179460X41667Ciência e Natura; Vol. 43 (2021): Continuous Publication; e38Ciência e Natura; v. 43 (2021): Publicação Contínua; e382179-460X0100-8307reponame:Revista Ciência e Natura (Online)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMporhttps://periodicos.ufsm.br/cienciaenatura/article/view/41667/pdfhttps://periodicos.ufsm.br/cienciaenatura/article/view/41667/htmlCopyright (c) 2021 Ciência e Naturainfo:eu-repo/semantics/openAccessNeu, Ismael Mario MárcioCargnelutti Filho, Albertode Bem, Cláudia MarquesKleinpaul, Jéssica AndiaraBandeira, Cirineu Tolfo2022-01-14T12:59:26Zoai:ojs.pkp.sfu.ca:article/41667Revistahttps://periodicos.ufsm.br/cienciaenatura/indexPUBhttps://periodicos.ufsm.br/cienciaenatura/oaicienciaenatura@ufsm.br || centraldeperiodicos@ufsm.br2179-460X0100-8307opendoar:2022-01-14T12:59:26Revista Ciência e Natura (Online) - Universidade Federal de Santa Maria (UFSM)false
dc.title.none.fl_str_mv Sample size for evaluation the of multicollinearity degree in productive traits of rye
Tamanho de amostra para avaliação do grau de multicolinearidade em caracteres produtivos de centeio
title Sample size for evaluation the of multicollinearity degree in productive traits of rye
spellingShingle Sample size for evaluation the of multicollinearity degree in productive traits of rye
Neu, Ismael Mario Márcio
Secale cereale L
Sampling design
Correlation
Multivariate analysis
Secale cereale L
Dimensionamento amostral
Correlação
Análise multivariada
title_short Sample size for evaluation the of multicollinearity degree in productive traits of rye
title_full Sample size for evaluation the of multicollinearity degree in productive traits of rye
title_fullStr Sample size for evaluation the of multicollinearity degree in productive traits of rye
title_full_unstemmed Sample size for evaluation the of multicollinearity degree in productive traits of rye
title_sort Sample size for evaluation the of multicollinearity degree in productive traits of rye
author Neu, Ismael Mario Márcio
author_facet Neu, Ismael Mario Márcio
Cargnelutti Filho, Alberto
de Bem, Cláudia Marques
Kleinpaul, Jéssica Andiara
Bandeira, Cirineu Tolfo
author_role author
author2 Cargnelutti Filho, Alberto
de Bem, Cláudia Marques
Kleinpaul, Jéssica Andiara
Bandeira, Cirineu Tolfo
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Neu, Ismael Mario Márcio
Cargnelutti Filho, Alberto
de Bem, Cláudia Marques
Kleinpaul, Jéssica Andiara
Bandeira, Cirineu Tolfo
dc.subject.por.fl_str_mv Secale cereale L
Sampling design
Correlation
Multivariate analysis
Secale cereale L
Dimensionamento amostral
Correlação
Análise multivariada
topic Secale cereale L
Sampling design
Correlation
Multivariate analysis
Secale cereale L
Dimensionamento amostral
Correlação
Análise multivariada
description The objectives of this work were to determine the sample size (number of plants) necessary to estimate the indicators of the of multicollinearity degree - condition number (CN), determinant of the correlation matrix (DET), and variance inflation factor (VIF) - in productive traits of rye and to verify the variability of the sample size between the indicators. Five and three uniformity trials were conducted with the cultivars BRS Progresso and Temprano, respectively, and seven productive traits were evaluated in 780 plants. Twenty-one cases were obtained from seven traits, combined five to five. In each case, 197 sample sizes were planned (20, 25, 30, ..., 1,000 plants) and in each size 2,000 resampling were performed, with replacement. For each resample the CN, DET and FIV were determined and the average among 2,000 estimates of each indicator of the multicollinearity degree was calculated. Then, for each case and indicator, the sample size was determined through three models: models of maximum modified curvature, segmented linear with plateau response, and segmented quadratic with plateau response. There was superiority the quadratic model segmented with plateau in adjusting the degree of multicollinearity according to the sample size for all indicators. There is a need greater sample size to detect multicollinearity when diagnosed by DET and for sizes larger than 101, 258 and 102 plants when diagnosing for the number of conditions, determinant and inflation factor performed, respectively.
publishDate 2022
dc.date.none.fl_str_mv 2022-01-14
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 https://periodicos.ufsm.br/cienciaenatura/article/view/41667
10.5902/2179460X41667
url https://periodicos.ufsm.br/cienciaenatura/article/view/41667
identifier_str_mv 10.5902/2179460X41667
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.ufsm.br/cienciaenatura/article/view/41667/pdf
https://periodicos.ufsm.br/cienciaenatura/article/view/41667/html
dc.rights.driver.fl_str_mv Copyright (c) 2021 Ciência e Natura
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Ciência e Natura
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
text/html
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
publisher.none.fl_str_mv Universidade Federal de Santa Maria
dc.source.none.fl_str_mv Ciência e Natura; Vol. 43 (2021): Continuous Publication; e38
Ciência e Natura; v. 43 (2021): Publicação Contínua; e38
2179-460X
0100-8307
reponame:Revista Ciência e Natura (Online)
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Revista Ciência e Natura (Online)
collection Revista Ciência e Natura (Online)
repository.name.fl_str_mv Revista Ciência e Natura (Online) - Universidade Federal de Santa Maria (UFSM)
repository.mail.fl_str_mv cienciaenatura@ufsm.br || centraldeperiodicos@ufsm.br
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