Type I error in multiple comparison tests in analysis of variance

Detalhes bibliográficos
Autor(a) principal: Rodrigues, Josiane
Data de Publicação: 2022
Outros Autores: Piedade, Sonia Maria De Stefano, Lara, Idemauro Antonio Rodrigues de, Henrique , Francisco Humberto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Acta Scientiarum. Agronomy (Online)
Texto Completo: http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/57742
Resumo: In a hypothesis test, a researcher initially fixes a type I error rate, that is, the probability of rejecting the null hypothesis given that it is true. In the case of means tests, it is important to present a type I error that is equal to the nominal pre-fixed level, such that this error remains unchanged across various scenarios, including the number of treatments, number of repetitions, and coefficient of variation. The purpose of this study is to analyse and compare the following multiple comparison tests for the control of both conditional and unconditional type I error rates, depending on a significant F-test in the analysis of variance: Tukey, Duncan, Fisher’s least significant difference, Student–Newman–Keuls (SNK), and Scheffé. As an application, we present a motivation study and develop a simulation study using the Monte Carlo method for a total of 64 scenarios. In each simulated scenario, we estimate the comparison-wise and experiment-wise error rates, conditional and unconditional on a significant result of the overall F-test of analysis of variance for each of the five multiple comparison tests evaluated. The results indicate that the application of the means tests based only on the significance of the F-test should be considered when determining the error rates, as this can change them. In addition, we find that Fisher’s test controls for the comparison-wise error rate, the Tukey and SNK tests control for the experiment-wise error rate, and the Duncan and Fisher tests control for the conditional experiment-wise error rate. Scheffé’s test does not control for any of the error rates considered.
id UEM-5_8a80af88c7c31a2c13913e73699740ea
oai_identifier_str oai:periodicos.uem.br/ojs:article/57742
network_acronym_str UEM-5
network_name_str Acta Scientiarum. Agronomy (Online)
repository_id_str
spelling Type I error in multiple comparison tests in analysis of variance Type I error in multiple comparison tests in analysis of variance comparison-wise error rate; experiment-wise error rate; means tests; Monte Carlo simulation.comparison-wise error rate; experiment-wise error rate; means tests; Monte Carlo simulation.In a hypothesis test, a researcher initially fixes a type I error rate, that is, the probability of rejecting the null hypothesis given that it is true. In the case of means tests, it is important to present a type I error that is equal to the nominal pre-fixed level, such that this error remains unchanged across various scenarios, including the number of treatments, number of repetitions, and coefficient of variation. The purpose of this study is to analyse and compare the following multiple comparison tests for the control of both conditional and unconditional type I error rates, depending on a significant F-test in the analysis of variance: Tukey, Duncan, Fisher’s least significant difference, Student–Newman–Keuls (SNK), and Scheffé. As an application, we present a motivation study and develop a simulation study using the Monte Carlo method for a total of 64 scenarios. In each simulated scenario, we estimate the comparison-wise and experiment-wise error rates, conditional and unconditional on a significant result of the overall F-test of analysis of variance for each of the five multiple comparison tests evaluated. The results indicate that the application of the means tests based only on the significance of the F-test should be considered when determining the error rates, as this can change them. In addition, we find that Fisher’s test controls for the comparison-wise error rate, the Tukey and SNK tests control for the experiment-wise error rate, and the Duncan and Fisher tests control for the conditional experiment-wise error rate. Scheffé’s test does not control for any of the error rates considered.In a hypothesis test, a researcher initially fixes a type I error rate, that is, the probability of rejecting the null hypothesis given that it is true. In the case of means tests, it is important to present a type I error that is equal to the nominal pre-fixed level, such that this error remains unchanged across various scenarios, including the number of treatments, number of repetitions, and coefficient of variation. The purpose of this study is to analyse and compare the following multiple comparison tests for the control of both conditional and unconditional type I error rates, depending on a significant F-test in the analysis of variance: Tukey, Duncan, Fisher’s least significant difference, Student–Newman–Keuls (SNK), and Scheffé. As an application, we present a motivation study and develop a simulation study using the Monte Carlo method for a total of 64 scenarios. In each simulated scenario, we estimate the comparison-wise and experiment-wise error rates, conditional and unconditional on a significant result of the overall F-test of analysis of variance for each of the five multiple comparison tests evaluated. The results indicate that the application of the means tests based only on the significance of the F-test should be considered when determining the error rates, as this can change them. In addition, we find that Fisher’s test controls for the comparison-wise error rate, the Tukey and SNK tests control for the experiment-wise error rate, and the Duncan and Fisher tests control for the conditional experiment-wise error rate. Scheffé’s test does not control for any of the error rates considered.Universidade Estadual de Maringá2022-11-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/5774210.4025/actasciagron.v45i1.57742Acta Scientiarum. Agronomy; Vol 45 (2023): Publicação contínua; e57742Acta Scientiarum. Agronomy; v. 45 (2023): Publicação contínua; e577421807-86211679-9275reponame:Acta Scientiarum. Agronomy (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/57742/751375155046Copyright (c) 2023 Acta Scientiarum. Agronomyhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessRodrigues, JosianePiedade, Sonia Maria De Stefano Lara, Idemauro Antonio Rodrigues de Henrique , Francisco Humberto2023-01-31T19:20:20Zoai:periodicos.uem.br/ojs:article/57742Revistahttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgronPUBhttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/oaiactaagron@uem.br||actaagron@uem.br|| edamasio@uem.br1807-86211679-9275opendoar:2023-01-31T19:20:20Acta Scientiarum. Agronomy (Online) - Universidade Estadual de Maringá (UEM)false
dc.title.none.fl_str_mv Type I error in multiple comparison tests in analysis of variance
Type I error in multiple comparison tests in analysis of variance
title Type I error in multiple comparison tests in analysis of variance
spellingShingle Type I error in multiple comparison tests in analysis of variance
Rodrigues, Josiane
comparison-wise error rate; experiment-wise error rate; means tests; Monte Carlo simulation.
comparison-wise error rate; experiment-wise error rate; means tests; Monte Carlo simulation.
title_short Type I error in multiple comparison tests in analysis of variance
title_full Type I error in multiple comparison tests in analysis of variance
title_fullStr Type I error in multiple comparison tests in analysis of variance
title_full_unstemmed Type I error in multiple comparison tests in analysis of variance
title_sort Type I error in multiple comparison tests in analysis of variance
author Rodrigues, Josiane
author_facet Rodrigues, Josiane
Piedade, Sonia Maria De Stefano
Lara, Idemauro Antonio Rodrigues de
Henrique , Francisco Humberto
author_role author
author2 Piedade, Sonia Maria De Stefano
Lara, Idemauro Antonio Rodrigues de
Henrique , Francisco Humberto
author2_role author
author
author
dc.contributor.author.fl_str_mv Rodrigues, Josiane
Piedade, Sonia Maria De Stefano
Lara, Idemauro Antonio Rodrigues de
Henrique , Francisco Humberto
dc.subject.por.fl_str_mv comparison-wise error rate; experiment-wise error rate; means tests; Monte Carlo simulation.
comparison-wise error rate; experiment-wise error rate; means tests; Monte Carlo simulation.
topic comparison-wise error rate; experiment-wise error rate; means tests; Monte Carlo simulation.
comparison-wise error rate; experiment-wise error rate; means tests; Monte Carlo simulation.
description In a hypothesis test, a researcher initially fixes a type I error rate, that is, the probability of rejecting the null hypothesis given that it is true. In the case of means tests, it is important to present a type I error that is equal to the nominal pre-fixed level, such that this error remains unchanged across various scenarios, including the number of treatments, number of repetitions, and coefficient of variation. The purpose of this study is to analyse and compare the following multiple comparison tests for the control of both conditional and unconditional type I error rates, depending on a significant F-test in the analysis of variance: Tukey, Duncan, Fisher’s least significant difference, Student–Newman–Keuls (SNK), and Scheffé. As an application, we present a motivation study and develop a simulation study using the Monte Carlo method for a total of 64 scenarios. In each simulated scenario, we estimate the comparison-wise and experiment-wise error rates, conditional and unconditional on a significant result of the overall F-test of analysis of variance for each of the five multiple comparison tests evaluated. The results indicate that the application of the means tests based only on the significance of the F-test should be considered when determining the error rates, as this can change them. In addition, we find that Fisher’s test controls for the comparison-wise error rate, the Tukey and SNK tests control for the experiment-wise error rate, and the Duncan and Fisher tests control for the conditional experiment-wise error rate. Scheffé’s test does not control for any of the error rates considered.
publishDate 2022
dc.date.none.fl_str_mv 2022-11-22
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/ActaSciAgron/article/view/57742
10.4025/actasciagron.v45i1.57742
url http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/57742
identifier_str_mv 10.4025/actasciagron.v45i1.57742
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/57742/751375155046
dc.rights.driver.fl_str_mv Copyright (c) 2023 Acta Scientiarum. Agronomy
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2023 Acta Scientiarum. Agronomy
https://creativecommons.org/licenses/by/4.0
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. Agronomy; Vol 45 (2023): Publicação contínua; e57742
Acta Scientiarum. Agronomy; v. 45 (2023): Publicação contínua; e57742
1807-8621
1679-9275
reponame:Acta Scientiarum. Agronomy (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. Agronomy (Online)
collection Acta Scientiarum. Agronomy (Online)
repository.name.fl_str_mv Acta Scientiarum. Agronomy (Online) - Universidade Estadual de Maringá (UEM)
repository.mail.fl_str_mv actaagron@uem.br||actaagron@uem.br|| edamasio@uem.br
_version_ 1799305901189890048