Maximum likelihood estimation of a social relations structural equation model

Steffen Nestler (), Oliver Lüdtke and Alexander Robitzsch
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Steffen Nestler: University of Münster
Oliver Lüdtke: Leibniz Institute for Science and Mathematics Education
Alexander Robitzsch: Leibniz Institute for Science and Mathematics Education

Psychometrika, 2020, vol. 85, issue 4, No 2, 870-889

Abstract: Abstract The social relations model (SRM) is widely used in psychology to investigate the components that underlie interpersonal perceptions, behaviors, and judgments. SRM researchers are often interested in investigating the multivariate relations between SRM effects. However, at present, it is not possible to investigate such relations without relying on a two-step approach that depends on potentially unreliable estimates of the true SRM effects. Here, we introduce a way to combine the SRM with the structural equation modeling (SEM) framework and show how the parameters of our combination can be estimated with a maximum likelihood (ML) approach. We illustrate the model with an example from personality psychology. We also investigate the statistical properties of the model in a small simulation study showing that our approach performs well in most simulation conditions. An R package (called srm) is available implementing the proposed methods.

Keywords: social relations model; structural equation modeling; maximum likelihood estimation (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11336-020-09728-z

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