Comparing N = 1 effect size indices in presence of autocorrelation

Generalization from single-case designs can be achieved by means of replicating individual studies across different experimental units and settings. When replications are available, their findings can be summarized using effect size measurements and integrated through meta-analyses. Several procedur...

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Detalles Bibliográficos
Autores: Manolov, Rumen, Solanas Pérez, Antonio
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2008
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:2445/34753
Acceso en línea:https://hdl.handle.net/2445/34753
Access Level:acceso abierto
Palabra clave:Investigació de cas únic
Correlació (Estadística)
Single subject research
Correlation (Statistics)
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spelling Comparing N = 1 effect size indices in presence of autocorrelationManolov, RumenSolanas Pérez, AntonioInvestigació de cas únicCorrelació (Estadística)Single subject researchCorrelation (Statistics)Generalization from single-case designs can be achieved by means of replicating individual studies across different experimental units and settings. When replications are available, their findings can be summarized using effect size measurements and integrated through meta-analyses. Several procedures are available for quantifying the magnitude of treatment"s effect in N = 1 designs and some of them are studied in the current paper. Monte Carlo simulations were employed to generate different data patterns (trend, level change, slope change). The experimental conditions simulated were defined by the degrees of serial dependence and phases" length. Out of all the effect size indices studied, the Percent of nonoverlapping data and standardized mean difference proved to be less affected by autocorrelation and perform better for shorter data series. The regression-based procedures proposed specifically for single-case designs did not differentiate between data patterns as well as simpler indices.Sage Publications2013201320082013info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersion16 p.application/pdfhttps://hdl.handle.net/2445/34753Articles 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: DOI: 10.1177/0145445508318866Behavior Modification, 2008, vol. 32, num. 6, p. 860-875http://dx.doi.org/10.1177/0145445508318866(c) Manolov, Rumen et al., 2008info:eu-repo/semantics/openAccessoai:recercat.cat:2445/347532026-05-29T05:05:01Z
dc.title.none.fl_str_mv Comparing N = 1 effect size indices in presence of autocorrelation
title Comparing N = 1 effect size indices in presence of autocorrelation
spellingShingle Comparing N = 1 effect size indices in presence of autocorrelation
Manolov, Rumen
Investigació de cas únic
Correlació (Estadística)
Single subject research
Correlation (Statistics)
title_short Comparing N = 1 effect size indices in presence of autocorrelation
title_full Comparing N = 1 effect size indices in presence of autocorrelation
title_fullStr Comparing N = 1 effect size indices in presence of autocorrelation
title_full_unstemmed Comparing N = 1 effect size indices in presence of autocorrelation
title_sort Comparing N = 1 effect size indices in presence of autocorrelation
dc.creator.none.fl_str_mv Manolov, Rumen
Solanas Pérez, Antonio
author Manolov, Rumen
author_facet Manolov, Rumen
Solanas Pérez, Antonio
author_role author
author2 Solanas Pérez, Antonio
author2_role author
dc.subject.none.fl_str_mv Investigació de cas únic
Correlació (Estadística)
Single subject research
Correlation (Statistics)
topic Investigació de cas únic
Correlació (Estadística)
Single subject research
Correlation (Statistics)
description Generalization from single-case designs can be achieved by means of replicating individual studies across different experimental units and settings. When replications are available, their findings can be summarized using effect size measurements and integrated through meta-analyses. Several procedures are available for quantifying the magnitude of treatment"s effect in N = 1 designs and some of them are studied in the current paper. Monte Carlo simulations were employed to generate different data patterns (trend, level change, slope change). The experimental conditions simulated were defined by the degrees of serial dependence and phases" length. Out of all the effect size indices studied, the Percent of nonoverlapping data and standardized mean difference proved to be less affected by autocorrelation and perform better for shorter data series. The regression-based procedures proposed specifically for single-case designs did not differentiate between data patterns as well as simpler indices.
publishDate 2008
dc.date.none.fl_str_mv 2008
2013
2013
2013
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/2445/34753
url https://hdl.handle.net/2445/34753
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Versió postprint del document publicat a: DOI: 10.1177/0145445508318866
Behavior Modification, 2008, vol. 32, num. 6, p. 860-875
http://dx.doi.org/10.1177/0145445508318866
dc.rights.none.fl_str_mv (c) Manolov, Rumen et al., 2008
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) Manolov, Rumen et al., 2008
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 16 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 15,811543

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