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Psychometrika

, Volume 82, Issue 4, pp 1162–1181 | Cite as

Tackling Longitudinal Round-Robin Data: A Social Relations Growth Model

  • Steffen NestlerEmail author
  • Katharina Geukes
  • Roos Hutteman
  • Mitja D. Back
Article

Abstract

The social relations model (SRM) is commonly used in the analysis of interpersonal judgments and behaviors that arise in groups. The SRM was developed only for use with cross-sectional data. Here, we introduce an extension of the SRM to longitudinal data. The social relations growth model represents a person’s repeated SRM judgments of another person as a function of time. We show how the model’s parameters can be estimated using restricted maximum likelihood, and how the effects of covariates on interindividual and interdyad variability in growth can be computed. An example is presented to illustrate the suggested approach. We also present the results of a small simulation study showing the suitability of the social relations growth model for the analysis of longitudinal SRM data.

Keywords

social relations model linear mixed model longitudinal data restricted maximum likelihood 

Notes

Acknowledgement

We are grateful to Sarah Humberg for very helpful comments on an earlier version of the manuscript.

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Copyright information

© The Psychometric Society 2016

Authors and Affiliations

  • Steffen Nestler
    • 1
    Email author
  • Katharina Geukes
    • 2
  • Roos Hutteman
    • 3
  • Mitja D. Back
    • 2
  1. 1.University of LeipzigLeipzigGermany
  2. 2.University of MünsterMünsterGermany
  3. 3.University of UtrechtUtrechtThe Netherlands

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