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

Steffen Nestler (), Katharina Geukes, Roos Hutteman and Mitja D. Back
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Steffen Nestler: University of Leipzig
Katharina Geukes: University of Münster
Roos Hutteman: University of Utrecht
Mitja D. Back: University of Münster

Psychometrika, 2017, vol. 82, issue 4, No 13, 1162-1181

Abstract: 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 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11336-016-9546-5

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