Por favor, use este identificador para citar o enlazar este ítem: https://repositorio.uca.edu.ar/handle/123456789/10326
Campo DC Valor Lengua/Idioma
dc.contributor.authorBringmann, Laura F.es
dc.contributor.authorVigo, Daniel Eduardoes
dc.contributor.authorBorsboom, Dennyes
dc.contributor.authorHamaker, Ellen L.es
dc.contributor.authorAubert, André E.es
dc.contributor.authorTuerlinckx, Francises
dc.date.accessioned2020-07-04T00:10:45Z-
dc.date.available2020-07-04T00:10:45Z-
dc.date.issued2017-
dc.identifier.citationBringmann, L. F., et al. Changing dynamics : time-varying autoregressive models using generalized additive modeling [en línea]. Postprint de artículo publicado en Psychological Methods. 2017, 22 (3). doi:10.1037/met0000085. Disponible en: https://repositorio.uca.edu.ar/handle/123456789/10326es
dc.identifier.issn1082-989X (impreso)-
dc.identifier.issn1939-1463 (online)-
dc.identifier.urihttps://repositorio.uca.edu.ar/handle/123456789/10326-
dc.description.abstractAbstract: In psychology, the use of intensive longitudinal data has steeply increased during the past decade. As a result, studying temporal dependencies in such data with autoregressive modeling is becoming common practice. However, standard autoregressive models are often suboptimal as they assume that parameters are time-invariant. This is problematic if changing dynamics (e.g., changes in the temporal dependency of a process) govern the time series. Often a change in the process, such as emotional well-being during therapy, is the very reason why it is interesting and important to study psychological dynamics. As a result, there is a need for an easily applicable method for studying such nonstationary processes that result from changing dynamics. In this article we present such a tool: the semiparametric TV-AR model. We show with a simulation study and an empirical application that the TV-AR model can approximate nonstationary processes well if there are at least 100 time points available and no unknown abrupt changes in the data. Notably, no prior knowledge of the processes that drive change in the dynamic structure is necessary. We conclude that the TV-AR model has significant potential for studying changing dynamics in psychology.es
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherAmerican Psychological Associationes
dc.rightsAcceso abierto*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.sourcePsychological Methods. 2017, 22 (3)es
dc.subjectSERIES TEMPORALESes
dc.subjectMETODOS ESTADISTICOSes
dc.subjectREGRESION LINEALes
dc.subjectPSICOLOGIAes
dc.subjectMODELOS MATEMATICOSes
dc.titleChanging dynamics : time-varying autoregressive models using generalized additive modelinges
dc.typeArtículoes
dc.identifier.doi10.1037/met0000085-
uca.disciplinaMEDICINAes
uca.issnrd1es
uca.affiliationFil: Bringmann, Laura F. University of Leuven. Department Quantitative Psychology and Individual Differences; Bélgicaes
uca.affiliationFil: Hamaker, Ellen L. University of Utrecht; Países Bajoses
uca.affiliationFil: Vigo, Daniel Eduardo. Pontificia Universidad Católica Argentina. Facultad de Ciencias Médicas. Instituto de Investigaciones Biomédicas; Argentinaes
uca.affiliationFil: Vigo, Daniel Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentinaes
uca.affiliationFil: Vigo, Daniel Eduardo. University of Leuven; Bélgicaes
uca.affiliationFil: Aubert, André E. University of Leuven; Bélgicaes
uca.affiliationFil: Borsboom, Denny. University of Amsterdam; Países Bajoses
uca.affiliationFil: Tuerlinckx, Francis. University of Leuven; Bélgicaes
uca.versionacceptedVersiones
item.grantfulltextopen-
item.fulltextWith Fulltext-
item.languageiso639-1en-
crisitem.author.deptInstituto de Investigaciones Biomédicas - BIOMED-
crisitem.author.deptLaboratorio de Cronofisiología-
crisitem.author.deptFacultad de Ciencias Médicas-
crisitem.author.deptFacultad de Ciencias Médicas-
crisitem.author.orcid0000-0003-2291-245X-
crisitem.author.parentorgFacultad de Ciencias Médicas-
crisitem.author.parentorgInstituto de Investigaciones Biomédicas - BIOMED-
crisitem.author.parentorgPontificia Universidad Católica Argentina-
crisitem.author.parentorgPontificia Universidad Católica Argentina-
Aparece en las colecciones: Artículos
Ficheros en este ítem:
Fichero Descripción Tamaño Formato
changing-dinamics-time-varying.pdf455,88 kBAdobe PDFVista previa
Visualizar/Abrir
Mostrar el registro sencillo del ítem

Visualizaciones de página(s)

143
comprobado en 27-mar-2024

Descarga(s)

1.282
comprobado en 27-mar-2024

Google ScholarTM

Consultar


Altmetric


Este ítem está sujeto a una licencia Creative Commons Licencia Creative Commons Creative Commons