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Analyzing Dyadic Data Using Grid-Sequence Analysis: Interdyad Differences in Intradyad Dynamics

Author

Listed:
  • Miriam Brinberg
  • Nilam Ram
  • Gizem Hülür
  • Timothy R Brick
  • Denis Gerstorf

Abstract

Objectives: Spouses are proximal contexts for and influence each other’s behaviors, particularly in old age. In this article, we forward an integrated approach that merges state space grid methods adapted from the dynamic systems literature with sequence analysis methods adapted from molecular biology into a “grid-sequence†method for studying interdyad differences in intradyad dynamics.MethodUsing dyadic data from 108 older couples (MAge = 75.18 years) with six within-day emotion and activity reports over 7 days, we illustrate how grid-sequence analysis can be used to identify a taxonomy of dyads with different emotion dynamics. Results: Results provide a basis for measuring a set of dyad-level variables that capture dynamic equilibrium, daily routines, and interdyad differences. Specifically, we identified four groups of dyads who differed in how their moment-to-moment happiness was organized, with some evidence that these patterns were related to dyad-level differences in agreement on amount of time spent with partner and in subjective health. Discussion: Methodologically, grid-sequence analysis extends the toolbox of techniques for analysis of dyadic experience sampling data. Substantively, we identify patterns of dyad-level microdynamics that may serve as new markers of risk/protective factors and potential points for intervention in older adults’ proximal context.

Suggested Citation

  • Miriam Brinberg & Nilam Ram & Gizem Hülür & Timothy R Brick & Denis Gerstorf, 2018. "Analyzing Dyadic Data Using Grid-Sequence Analysis: Interdyad Differences in Intradyad Dynamics," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 73(1), pages 5-18.
  • Handle: RePEc:oup:geronb:v:73:y:2018:i:1:p:5-18.
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    File URL: http://hdl.handle.net/10.1093/geronb/gbw160
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    References listed on IDEAS

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    1. Wickham, Hadley, 2007. "Reshaping Data with the reshape Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 21(i12).
    2. Gabadinho, Alexis & Ritschard, Gilbert & Müller, Nicolas S & Studer, Matthias, 2011. "Analyzing and Visualizing State Sequences in R with TraMineR," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i04).
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