Analysis of variance of primary data on plant growth analysis

Detalhes bibliográficos
Autor(a) principal: Araújo, Adelson Paulo
Data de Publicação: 2003
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Pesquisa Agropecuária Brasileira (Online)
Texto Completo: https://seer.sct.embrapa.br/index.php/pab/article/view/6537
Resumo: Plant growth analysis presents difficulties related to statistical comparison of growth rates, and the analysis of variance of primary data could guide the interpretation of results. The objective of this work was to evaluate the analysis of variance of data from distinct harvests of an experiment, focusing especially on the homogeneity of variances and the choice of an adequate ANOVA model. Data from five experiments covering different crops and growth conditions were used. From the total number of variables, 19% were originally homoscedastic, 60% became homoscedastic after logarithmic transformation, and 21% remained heteroscedastic after transformation. Data transformation did not affect the F test in one experiment, whereas in the other experiments transformation modified the F test usually reducing the number of significant effects. Even when transformation has not altered the F test, mean comparisons led to divergent interpretations. The mixed ANOVA model, considering harvest as a random effect, reduced the number of significant effects of every factor which had the F test modified by this model. Examples illustrated that analysis of variance of primary variables provides a tool for identifying significant differences in growth rates. The analysis of variance imposes restrictions to experimental design thereby eliminating some advantages of the functional growth analysis.
id EMBRAPA-4_fe7022b36310c8d994d59bc1119884c3
oai_identifier_str oai:ojs.seer.sct.embrapa.br:article/6537
network_acronym_str EMBRAPA-4
network_name_str Pesquisa Agropecuária Brasileira (Online)
repository_id_str
spelling Analysis of variance of primary data on plant growth analysisAnálise de variância dos dados primários na análise de crescimento vegetalANOVA model; statistic; phosphorus; common bean; ricemodelo de ANOVA; estatística; fósforo; feijão; arrozPlant growth analysis presents difficulties related to statistical comparison of growth rates, and the analysis of variance of primary data could guide the interpretation of results. The objective of this work was to evaluate the analysis of variance of data from distinct harvests of an experiment, focusing especially on the homogeneity of variances and the choice of an adequate ANOVA model. Data from five experiments covering different crops and growth conditions were used. From the total number of variables, 19% were originally homoscedastic, 60% became homoscedastic after logarithmic transformation, and 21% remained heteroscedastic after transformation. Data transformation did not affect the F test in one experiment, whereas in the other experiments transformation modified the F test usually reducing the number of significant effects. Even when transformation has not altered the F test, mean comparisons led to divergent interpretations. The mixed ANOVA model, considering harvest as a random effect, reduced the number of significant effects of every factor which had the F test modified by this model. Examples illustrated that analysis of variance of primary variables provides a tool for identifying significant differences in growth rates. The analysis of variance imposes restrictions to experimental design thereby eliminating some advantages of the functional growth analysis.A análise de crescimento vegetal apresenta dificuldades relacionadas à comparação estatística das curvas de crescimento, e a análise de variância dos dados primários pode orientar a interpretação dos resultados. Este trabalho objetivou avaliar a análise de variância de dados de distintas coletas de um experimento, abordando particularmente a homogeneidade das variâncias e a escolha do modelo adequado de ANOVA. Foram utilizados dados de cinco experimentos com diferentes culturas e condições de crescimento. Do total de variáveis, 19% foram originalmente homocedásticas, 60% tornaram-se homocedásticas após transformação logarítmica, e 21% mantiveram-se heterocedásticas após transformação. A transformação dos dados não afetou o teste F em um experimento, enquanto nos demais experimentos a transformação o modificou geralmente com redução dos efeitos significativos. Mesmo quando a transformação não afetou o teste F, comparações de médias induziram a diferentes interpretações. O modelo de ANOVA misto, considerando a coleta como um efeito aleatório, reduziu o número de efeitos significativos de todos os fatores modificados por este modelo. Alguns exemplos ilustram que a análise de variância dos dados primários constitui uma ferramenta na identificação de efeitos significativos nas taxas de crescimento. A análise de variância impõe restrições ao delineamento experimental, eliminando algumas vantagens da análise funcional de crescimento.Pesquisa Agropecuaria BrasileiraPesquisa Agropecuária BrasileiraAraújo, Adelson Paulo2003-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.sct.embrapa.br/index.php/pab/article/view/6537Pesquisa Agropecuaria Brasileira; v.38, n.1, jan. 2003; 1-10Pesquisa Agropecuária Brasileira; v.38, n.1, jan. 2003; 1-101678-39210100-104xreponame:Pesquisa Agropecuária Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAenghttps://seer.sct.embrapa.br/index.php/pab/article/view/6537/3594info:eu-repo/semantics/openAccess2010-08-13T17:22:28Zoai:ojs.seer.sct.embrapa.br:article/6537Revistahttp://seer.sct.embrapa.br/index.php/pabPRIhttps://old.scielo.br/oai/scielo-oai.phppab@sct.embrapa.br || sct.pab@embrapa.br1678-39210100-204Xopendoar:2010-08-13T17:22:28Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Analysis of variance of primary data on plant growth analysis
Análise de variância dos dados primários na análise de crescimento vegetal
title Analysis of variance of primary data on plant growth analysis
spellingShingle Analysis of variance of primary data on plant growth analysis
Araújo, Adelson Paulo
ANOVA model; statistic; phosphorus; common bean; rice
modelo de ANOVA; estatística; fósforo; feijão; arroz
title_short Analysis of variance of primary data on plant growth analysis
title_full Analysis of variance of primary data on plant growth analysis
title_fullStr Analysis of variance of primary data on plant growth analysis
title_full_unstemmed Analysis of variance of primary data on plant growth analysis
title_sort Analysis of variance of primary data on plant growth analysis
author Araújo, Adelson Paulo
author_facet Araújo, Adelson Paulo
author_role author
dc.contributor.none.fl_str_mv

dc.contributor.author.fl_str_mv Araújo, Adelson Paulo
dc.subject.por.fl_str_mv ANOVA model; statistic; phosphorus; common bean; rice
modelo de ANOVA; estatística; fósforo; feijão; arroz
topic ANOVA model; statistic; phosphorus; common bean; rice
modelo de ANOVA; estatística; fósforo; feijão; arroz
description Plant growth analysis presents difficulties related to statistical comparison of growth rates, and the analysis of variance of primary data could guide the interpretation of results. The objective of this work was to evaluate the analysis of variance of data from distinct harvests of an experiment, focusing especially on the homogeneity of variances and the choice of an adequate ANOVA model. Data from five experiments covering different crops and growth conditions were used. From the total number of variables, 19% were originally homoscedastic, 60% became homoscedastic after logarithmic transformation, and 21% remained heteroscedastic after transformation. Data transformation did not affect the F test in one experiment, whereas in the other experiments transformation modified the F test usually reducing the number of significant effects. Even when transformation has not altered the F test, mean comparisons led to divergent interpretations. The mixed ANOVA model, considering harvest as a random effect, reduced the number of significant effects of every factor which had the F test modified by this model. Examples illustrated that analysis of variance of primary variables provides a tool for identifying significant differences in growth rates. The analysis of variance imposes restrictions to experimental design thereby eliminating some advantages of the functional growth analysis.
publishDate 2003
dc.date.none.fl_str_mv 2003-01-01
dc.type.none.fl_str_mv
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://seer.sct.embrapa.br/index.php/pab/article/view/6537
url https://seer.sct.embrapa.br/index.php/pab/article/view/6537
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://seer.sct.embrapa.br/index.php/pab/article/view/6537/3594
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 Pesquisa Agropecuaria Brasileira
Pesquisa Agropecuária Brasileira
publisher.none.fl_str_mv Pesquisa Agropecuaria Brasileira
Pesquisa Agropecuária Brasileira
dc.source.none.fl_str_mv Pesquisa Agropecuaria Brasileira; v.38, n.1, jan. 2003; 1-10
Pesquisa Agropecuária Brasileira; v.38, n.1, jan. 2003; 1-10
1678-3921
0100-104x
reponame:Pesquisa Agropecuária Brasileira (Online)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Pesquisa Agropecuária Brasileira (Online)
collection Pesquisa Agropecuária Brasileira (Online)
repository.name.fl_str_mv Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv pab@sct.embrapa.br || sct.pab@embrapa.br
_version_ 1793416701760503808

Registros relacionados