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A dynamic social relations model for clustered longitudinal dyadic data with continuous or ordinal responses

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  • Pillinger, Rebecca
  • Steele, Fiona
  • Leckie, George
  • Jenkins, Jennifer

Abstract

Social relations models allow the identification of cluster, actor, partner, and relationship effects when analysing clustered dyadic data on interactions between individuals or other units of analysis. We propose an extension of this model which handles longitudinal data and incorporates dynamic structure, where the response may be continuous, binary, or ordinal. This allows the disentangling of the relationship effects from temporal fluctuation and measurement error and the investigation of whether individuals respond to their partner’s behaviour at the previous observation. We motivate and illustrate the model with an application to Canadian data on pairs of individuals within families observed working together on a conflict discussion task.

Suggested Citation

  • Pillinger, Rebecca & Steele, Fiona & Leckie, George & Jenkins, Jennifer, 2024. "A dynamic social relations model for clustered longitudinal dyadic data with continuous or ordinal responses," LSE Research Online Documents on Economics 119988, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:119988
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    References listed on IDEAS

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    1. Binder, Michael & Hsiao, Cheng & Pesaran, M. Hashem, 2005. "Estimation And Inference In Short Panel Vector Autoregressions With Unit Roots And Cointegration," Econometric Theory, Cambridge University Press, vol. 21(4), pages 795-837, August.
    2. Stephen Pudney, 2008. "The dynamics of perception: modelling subjective wellbeing in a short panel," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 21-40, January.
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