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Latent Reciprocal Engagement and Accuracy Variables in Social Relations Structural Equation Modeling.

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This study enhances the social relations model (SRM) for analyzing dyadic interactions. Findings show reciprocal mimicry increases liking, while overestimating popularity decreases it.

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Accuracydyadic datareciprocityround-robinsocial relations modelstructural equation modeling

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Area of Science:

  • Social Psychology
  • Quantitative Psychology
  • Behavioral Science

Background:

  • The social relations model (SRM) is standard for dyadic data in round-robin designs.
  • SRM estimates reciprocity and accuracy of judgments at individual and dyadic levels.
  • Existing SRM lacks detailed analysis of inter-individual differences in reciprocal engagement and accuracy.

Purpose of the Study:

  • To modify the multiple indicator SRM to capture inter-individual and inter-dyadic differences in reciprocal engagement.
  • To analyze inter-individual differences in reciprocal accuracy within the SRM framework.
  • To apply these enhanced models to real-world dyadic interaction data.

Main Methods:

  • Utilized structural equation modeling within the social relations framework.
  • Applied stochastic measurement and classical test theory principles.
  • Modified the multiple indicator SRM for enhanced analysis of dyadic data.

Main Results:

  • People engaging in reciprocal mimicry are more liked post-interaction.
  • Overestimating one's own popularity is linked to being liked less.
  • The enhanced SRM effectively captures inter-individual and inter-dyadic differences.

Conclusions:

  • The modified SRM provides a more nuanced understanding of dyadic social dynamics.
  • Reciprocal mimicry and accurate self-perception of popularity are key to social liking.
  • The enhanced models offer valuable applications for studying social interactions.