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A protocol for analyzing repeated measures of online group behavior

In this article, we feature a novel protocol that enables the analysis of repeated measures of online group behavior. The protocol accounts for (1) the nested hierarchy of the data with weeks nested in persons, and persons nested in weeks, and (2) the temporal nature of the behavior at the early, mi...

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Detalles Bibliográficos
Autores principales: Courtney, Matthew G.R., Costley, Jamie, Fanguy, Mik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8987404/
https://www.ncbi.nlm.nih.gov/pubmed/35402171
http://dx.doi.org/10.1016/j.mex.2022.101667
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author Courtney, Matthew G.R.
Costley, Jamie
Fanguy, Mik
author_facet Courtney, Matthew G.R.
Costley, Jamie
Fanguy, Mik
author_sort Courtney, Matthew G.R.
collection PubMed
description In this article, we feature a novel protocol that enables the analysis of repeated measures of online group behavior. The protocol accounts for (1) the nested hierarchy of the data with weeks nested in persons, and persons nested in weeks, and (2) the temporal nature of the behavior at the early, mid, and late periods of each week. To manage and analyze such data in a general way, we first give an illustration of the data structure. Thereafter, we propose a five-step Courtney-Fanguy-Costley protocol that (1) considers the data structure, (2) defines the levels of data, (3) considers variable variation, timing, and necessary aggregation, (4) ensures necessary variation, and (5) specifies null and mixed-effects models. We also provide exemplary R code for readers to replicate our approach. • A general five-step protocol for analyzing repeated measures of online group behavior is offered. • A description of the complex nested data structure is offered. • Users can simulate data in R to run through the protocol.
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spelling pubmed-89874042022-04-08 A protocol for analyzing repeated measures of online group behavior Courtney, Matthew G.R. Costley, Jamie Fanguy, Mik MethodsX Method Article In this article, we feature a novel protocol that enables the analysis of repeated measures of online group behavior. The protocol accounts for (1) the nested hierarchy of the data with weeks nested in persons, and persons nested in weeks, and (2) the temporal nature of the behavior at the early, mid, and late periods of each week. To manage and analyze such data in a general way, we first give an illustration of the data structure. Thereafter, we propose a five-step Courtney-Fanguy-Costley protocol that (1) considers the data structure, (2) defines the levels of data, (3) considers variable variation, timing, and necessary aggregation, (4) ensures necessary variation, and (5) specifies null and mixed-effects models. We also provide exemplary R code for readers to replicate our approach. • A general five-step protocol for analyzing repeated measures of online group behavior is offered. • A description of the complex nested data structure is offered. • Users can simulate data in R to run through the protocol. Elsevier 2022-03-22 /pmc/articles/PMC8987404/ /pubmed/35402171 http://dx.doi.org/10.1016/j.mex.2022.101667 Text en © 2022 The Author(s). Published by Elsevier B.V. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Method Article
Courtney, Matthew G.R.
Costley, Jamie
Fanguy, Mik
A protocol for analyzing repeated measures of online group behavior
title A protocol for analyzing repeated measures of online group behavior
title_full A protocol for analyzing repeated measures of online group behavior
title_fullStr A protocol for analyzing repeated measures of online group behavior
title_full_unstemmed A protocol for analyzing repeated measures of online group behavior
title_short A protocol for analyzing repeated measures of online group behavior
title_sort protocol for analyzing repeated measures of online group behavior
topic Method Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8987404/
https://www.ncbi.nlm.nih.gov/pubmed/35402171
http://dx.doi.org/10.1016/j.mex.2022.101667
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