Dyadic analysis and the reciprocal one-with-many model: Extending the study of interpersonal processes with intensive longitudinal data

Newly available data streams from experience sampling studies and social media are providing new opportunities to study individuals’ dyadic relations. The “one-with-many” (OWM) model (Kenny et al., 2006; Kenny & Winquist, 2001) was specifically constructed for and is used to examine features of multiple dyadic relationships that one set of focal persons (e.g., therapists, physicians) has with others (e.g., multiple clients, multiple patients). Originally, the OWM model was constructed for and applied to cross-sectional data. However, the model can be extended to accommodate and may be particularly useful for the analysis of intensive repeated measures data now being obtained through experience sampling and social media. This article (a) provides a practical tutorial on fitting the OWM model, (b) describes how the OWM model is extended for analysis of repeated measures data, and (c) illustrates application of the OWM model using reports about interpersonal behavior and benefits individuals experienced in 64,111 social interactions during 9 weeks of study (N = 150). Our presentation highlights the utility of the OWM model for examining interpersonal processes in everyday life.

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Work Title Dyadic analysis and the reciprocal one-with-many model: Extending the study of interpersonal processes with intensive longitudinal data
Access
Open Access
Creators
  1. Miriam Brinberg
  2. Nilam Ram
  3. David E Conroy
  4. Aaron L Pincus
  5. Denis Gerstorf
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. Psychological Methods
Publication Date January 1, 2021
Publisher Identifier (DOI)
  1. https://doi.org/10.1037/met0000380
Deposited July 14, 2021

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  • Created

    July 14, 2021 11:10 by Researcher Metadata Database

  • Added Brinberg_et_al__2021_.pdf

    July 14, 2021 11:10 by Researcher Metadata Database

  • Added Creator Miriam Brinberg

    July 14, 2021 11:10 by Researcher Metadata Database

  • Added Creator N Ram

    July 14, 2021 11:10 by Researcher Metadata Database

  • Added Creator D E Conroy

    July 14, 2021 11:10 by Researcher Metadata Database

  • Added Creator D E Conroy

    July 14, 2021 11:10 by Researcher Metadata Database

  • Added Creator Aaron L Pincus

    July 14, 2021 11:10 by Researcher Metadata Database

  • Added Creator Aaron L Pincus

    July 14, 2021 11:10 by Researcher Metadata Database

  • Added Creator Denis Gerstorf

    July 14, 2021 11:10 by Researcher Metadata Database

  • Added Creator Denis Gerstorf

    July 14, 2021 11:10 by Researcher Metadata Database

  • Published

    July 14, 2021 11:10 by Researcher Metadata Database

  • Updated

    February 28, 2022 22:44 by [unknown user]

  • Updated

    March 22, 2022 16:17 by [unknown user]

  • Updated Work Title, Publisher Identifier (DOI), Description Show Changes

    August 31, 2022 10:03 by aee32

    Work Title
    • Dyadic analysis and the reciprocal one-with-many model: Extending study of interpersonal processes with intensive longitudinal data
    • Dyadic analysis and the reciprocal one-with-many model: Extending the study of interpersonal processes with intensive longitudinal data
    Publisher Identifier (DOI)
    • https://doi.org/10.1037/met0000380
    Description
    • Newly available data streams from experience sampling studies and social media are providing new
    • opportunities to study individuals’ dyadic relations. The “one-with-many” (OWM) model (Kenny et al.,
    • 2006; Kenny & Winquist, 2001) was specifically constructed for and is used to examine features of
    • multiple dyadic relationships that one set of focal persons (e.g., therapists, physicians) has with others
    • (e.g., multiple clients, multiple patients). Originally, the OWM model was constructed for and applied to
    • cross-sectional data. However, the model can be extended to accommodate and may be particularly
    • useful for the analysis of intensive repeated measures data now being obtained through experience
    • sampling and social media. This article (a) provides a practical tutorial on fitting the OWM model, (b)
    • describes how the OWM model is extended for analysis of repeated measures data, and (c) illustrates
    • application of the OWM model using reports about interpersonal behavior and benefits individuals
    • experienced in 64,111 social interactions during 9 weeks of study (N  150). Our presentation highlights
    • the utility of the OWM model for examining interpersonal processes in everyday life.
    • Newly available data streams from experience sampling studies and social media are providing new opportunities to study individuals’ dyadic relations. The “one-with-many” (OWM) model (Kenny et al., 2006; Kenny & Winquist, 2001) was specifically constructed for and is used to examine features of multiple dyadic relationships that one set of focal persons (e.g., therapists, physicians) has with others (e.g., multiple clients, multiple patients). Originally, the OWM model was constructed for and applied to cross-sectional data. However, the model can be extended to accommodate and may be particularly useful for the analysis of intensive repeated measures data now being obtained through experience sampling and social media. This article (a) provides a practical tutorial on fitting the OWM model, (b) describes how the OWM model is extended for analysis of repeated measures data, and (c) illustrates application of the OWM model using reports about interpersonal behavior and benefits individuals experienced in 64,111 social interactions during 9 weeks of study (_N_ = 150). Our presentation highlights the utility of the OWM model for examining interpersonal processes in everyday life.
  • Deleted Creator N Ram

    August 31, 2022 10:07 by aee32

  • Deleted Creator D E Conroy

    August 31, 2022 10:07 by aee32

  • Deleted Creator D E Conroy

    August 31, 2022 10:07 by aee32

  • Deleted Creator Aaron L Pincus

    August 31, 2022 10:07 by aee32

  • Deleted Creator Denis Gerstorf

    August 31, 2022 10:07 by aee32

  • Updated Creator Aaron L Pincus

    August 31, 2022 10:07 by aee32

  • Updated Creator Denis Gerstorf

    August 31, 2022 10:07 by aee32

  • Added Creator Nilam Ram

    August 31, 2022 10:07 by aee32

  • Added Creator David E Conroy

    August 31, 2022 10:07 by aee32