Modeling Longitudinal Dyadic Processes in Family Research.
In this article, several dyadic analyses are applied to illustrate how they can be used to answer distinct research questions regarding associations between dyad members over time (longitudinal interdependence). This article focuses on how to conceptualize and empirically assess distinct dyadic proc...
| Publicado en: | Journal of Family Psychology Vol. 35; no. 7; pp. 994 - 1007 |
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| Autores principales: | , , |
| Formato: | Artículo |
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American Psychological Association
Oct2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=161849334&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 161849334 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 08933200 JFY jtl: Journal of Family Psychology issn: 08933200 maglogo: N pubinfo: dt: Oct2021 vid: 35 iid: 7 pid: 34 pub: American Psychological Association artinfo: ui: 161849334 10.1037/fam0000862 ppf: 994 ppct: 13 formats: tig: atl: Modeling Longitudinal Dyadic Processes in Family Research. aug: au: Lee, Tae Kyoung Wickrama, Kandauda A. S. O'Neal, Catherine Walker affil: Department of Public Health Sciences, University of Miami Department of Human Development and Family Science, University of Georgia su: Family research Marriage Autoregressive models Research questions Parallel processing sug: subj: Family research Marriage Autoregressive models Research questions Parallel processing keyword: couple psychopathology dynamic dyadic processes parallel change processes structural equation modeling time-sequential processes couple psychopathology dynamic dyadic processes parallel change processes structural equation modeling time-sequential processes ab: In this article, several dyadic analyses are applied to illustrate how they can be used to answer distinct research questions regarding associations between dyad members over time (longitudinal interdependence). This article focuses on how to conceptualize and empirically assess distinct dyadic processes, including time-sequential processes involving change in rank-order, parallel change processes involving intra-individual changes, dynamic dyadic processes involving both intra-individual changes and time-specific deviations (from intra-individual change), and accelerated dyadic processes involving acceleration of intra-individual change. These dyadic processes are depicted by four different dyadic models; a cross-lagged autoregressive model, a dyadic latent growth model (with and without structured residuals), and a dyadic latent change score model, respectively. These four longitudinal dyadic models are illustrated using a sample of 251 husbands and wives in enduring marriages. Each model focuses on a different dyadic process demonstrating distinct ways to empirically assess longitudinal interdependence; thus, when analyzing data, dyadic researchers must weigh the advantages and disadvantages of each and select the modeling approach that is most appropriate for the research question. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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