Cargando…

Bayesian estimation of explained variance in ANOVA designs

We propose to use the squared multiple correlation coefficient as an effect size measure for experimental analysis‐of‐variance designs and to use Bayesian methods to estimate its posterior distribution. We provide the expressions for the squared multiple, semipartial, and partial correlation coeffic...

Descripción completa

Detalles Bibliográficos
Autores principales: Marsman, Maarten, Waldorp, Lourens, Dablander, Fabian, Wagenmakers, Eric‐Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6618269/
https://www.ncbi.nlm.nih.gov/pubmed/31341338
http://dx.doi.org/10.1111/stan.12173
_version_ 1783433882330202112
author Marsman, Maarten
Waldorp, Lourens
Dablander, Fabian
Wagenmakers, Eric‐Jan
author_facet Marsman, Maarten
Waldorp, Lourens
Dablander, Fabian
Wagenmakers, Eric‐Jan
author_sort Marsman, Maarten
collection PubMed
description We propose to use the squared multiple correlation coefficient as an effect size measure for experimental analysis‐of‐variance designs and to use Bayesian methods to estimate its posterior distribution. We provide the expressions for the squared multiple, semipartial, and partial correlation coefficients corresponding to four commonly used analysis‐of‐variance designs and illustrate our contribution with two worked examples.
format Online
Article
Text
id pubmed-6618269
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-66182692019-07-22 Bayesian estimation of explained variance in ANOVA designs Marsman, Maarten Waldorp, Lourens Dablander, Fabian Wagenmakers, Eric‐Jan Stat Neerl Original Articles We propose to use the squared multiple correlation coefficient as an effect size measure for experimental analysis‐of‐variance designs and to use Bayesian methods to estimate its posterior distribution. We provide the expressions for the squared multiple, semipartial, and partial correlation coefficients corresponding to four commonly used analysis‐of‐variance designs and illustrate our contribution with two worked examples. John Wiley and Sons Inc. 2019-03-27 2019-08 /pmc/articles/PMC6618269/ /pubmed/31341338 http://dx.doi.org/10.1111/stan.12173 Text en © 2019 The Authors. Statistica Neerlandica published by John Wiley & Sons Ltd on behalf of VVS. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Marsman, Maarten
Waldorp, Lourens
Dablander, Fabian
Wagenmakers, Eric‐Jan
Bayesian estimation of explained variance in ANOVA designs
title Bayesian estimation of explained variance in ANOVA designs
title_full Bayesian estimation of explained variance in ANOVA designs
title_fullStr Bayesian estimation of explained variance in ANOVA designs
title_full_unstemmed Bayesian estimation of explained variance in ANOVA designs
title_short Bayesian estimation of explained variance in ANOVA designs
title_sort bayesian estimation of explained variance in anova designs
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6618269/
https://www.ncbi.nlm.nih.gov/pubmed/31341338
http://dx.doi.org/10.1111/stan.12173
work_keys_str_mv AT marsmanmaarten bayesianestimationofexplainedvarianceinanovadesigns
AT waldorplourens bayesianestimationofexplainedvarianceinanovadesigns
AT dablanderfabian bayesianestimationofexplainedvarianceinanovadesigns
AT wagenmakersericjan bayesianestimationofexplainedvarianceinanovadesigns