How can single-case data be analyzed? Software resources, tutorial, and reflections on analysis

The present article aims to present a series of software developments in the quantitative analysis of data obtained via single-case experimental designs (SCEDs), as well as the tutorial describing these developments. The tutorial focuses on software implementations based on freely available platform...

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Detalles Bibliográficos
Autores: Manolov, Rumen, Moeyaert, Mariola
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2017
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/108579
Acceso en línea:https://hdl.handle.net/2445/108579
Access Level:acceso abierto
Palabra clave:Investigació de cas únic
Programari
Single subject research
Computer software
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spelling How can single-case data be analyzed? Software resources, tutorial, and reflections on analysisManolov, RumenMoeyaert, MariolaInvestigació de cas únicProgramariSingle subject researchComputer softwareThe present article aims to present a series of software developments in the quantitative analysis of data obtained via single-case experimental designs (SCEDs), as well as the tutorial describing these developments. The tutorial focuses on software implementations based on freely available platforms such as R and aims to bring statistical advances closer to applied researchers and help them become autonomous agents in the data analysis stage of a study. The range of analyses dealt with in the tutorial is illustrated on a typical single-case dataset, relying heavily on graphical data representations. We illustrate how visual and quantitative analyses can be used jointly, giving complementary information and helping the researcher decide whether there is an intervention effect, how large it is, and whether it is practically significant. To help applied researchers in the use of the analyses, we have organized the data in the different ways required by the different analytical procedures and made these data available online. We also provide Internet links to all free software available, as well as all the main references to the analytical techniques. Finally, we suggest that appropriate and informative data analysis is likely to be a step forward in documenting and communicating results and also for increasing the scientific credibility of SCEDs.SAGE Publications2017201720172017info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersion75 p.application/pdfhttps://hdl.handle.net/2445/108579Articles publicats en revistes (Psicologia Social i Psicologia Quantitativa)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésVersió postprint del document publicat a: https://doi.org/10.1177/0145445516664307Behavior Modification, 2017, vol. 41, num. 2, p. 179-228https://doi.org/10.1177/0145445516664307(c) Manolov, Rumen et al., 2017info:eu-repo/semantics/openAccessoai:recercat.cat:2445/1085792026-05-29T05:05:01Z
dc.title.none.fl_str_mv How can single-case data be analyzed? Software resources, tutorial, and reflections on analysis
title How can single-case data be analyzed? Software resources, tutorial, and reflections on analysis
spellingShingle How can single-case data be analyzed? Software resources, tutorial, and reflections on analysis
Manolov, Rumen
Investigació de cas únic
Programari
Single subject research
Computer software
title_short How can single-case data be analyzed? Software resources, tutorial, and reflections on analysis
title_full How can single-case data be analyzed? Software resources, tutorial, and reflections on analysis
title_fullStr How can single-case data be analyzed? Software resources, tutorial, and reflections on analysis
title_full_unstemmed How can single-case data be analyzed? Software resources, tutorial, and reflections on analysis
title_sort How can single-case data be analyzed? Software resources, tutorial, and reflections on analysis
dc.creator.none.fl_str_mv Manolov, Rumen
Moeyaert, Mariola
author Manolov, Rumen
author_facet Manolov, Rumen
Moeyaert, Mariola
author_role author
author2 Moeyaert, Mariola
author2_role author
dc.subject.none.fl_str_mv Investigació de cas únic
Programari
Single subject research
Computer software
topic Investigació de cas únic
Programari
Single subject research
Computer software
description The present article aims to present a series of software developments in the quantitative analysis of data obtained via single-case experimental designs (SCEDs), as well as the tutorial describing these developments. The tutorial focuses on software implementations based on freely available platforms such as R and aims to bring statistical advances closer to applied researchers and help them become autonomous agents in the data analysis stage of a study. The range of analyses dealt with in the tutorial is illustrated on a typical single-case dataset, relying heavily on graphical data representations. We illustrate how visual and quantitative analyses can be used jointly, giving complementary information and helping the researcher decide whether there is an intervention effect, how large it is, and whether it is practically significant. To help applied researchers in the use of the analyses, we have organized the data in the different ways required by the different analytical procedures and made these data available online. We also provide Internet links to all free software available, as well as all the main references to the analytical techniques. Finally, we suggest that appropriate and informative data analysis is likely to be a step forward in documenting and communicating results and also for increasing the scientific credibility of SCEDs.
publishDate 2017
dc.date.none.fl_str_mv 2017
2017
2017
2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/108579
url https://hdl.handle.net/2445/108579
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Versió postprint del document publicat a: https://doi.org/10.1177/0145445516664307
Behavior Modification, 2017, vol. 41, num. 2, p. 179-228
https://doi.org/10.1177/0145445516664307
dc.rights.none.fl_str_mv (c) Manolov, Rumen et al., 2017
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) Manolov, Rumen et al., 2017
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 75 p.
application/pdf
dc.publisher.none.fl_str_mv SAGE Publications
publisher.none.fl_str_mv SAGE Publications
dc.source.none.fl_str_mv Articles publicats en revistes (Psicologia Social i Psicologia Quantitativa)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812455

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