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Tutorial: Distinguishable and Exchangeable Dyads: Bayesian Multilevel Modelling

Cross-sectional and intensive longitudinal APIM and DIM

DOI

Developed by Pascal Küng, Postdoctoral Researcher at the University of Zurich. OSF profile.

Access the tutorial

Choose the interactive slide deck, the archival PDF, or one of the concise model guides:


Reproduce everything locally

If you want to run all analyses or rebuild the slides locally:

  1. Download the latest release or clone the repository.

  2. Open the 00DyadicDataAnalysis.Rproj.

  3. Open the presentation DyadicDataAnalysis.Rmd.

  4. Restore the project packages in the R console:

    renv::restore()
  5. To run the Bayesian models, install CmdStan:

    cmdstanr::check_cmdstan_toolchain(fix = TRUE)
    cmdstanr::install_cmdstan()
  6. Run the code interactively, or rebuild either output from the terminal:

    quarto render DyadicDataAnalysis.Rmd --to revealjs --output DyadicDataAnalysis.html
    quarto render DyadicDataAnalysis.Rmd --to pdf --output dyadic-data-analysis-tutorial.pdf

Both outputs are generated from the same format-aware source. Interactive elements are included only in HTML; the PDF uses static replacements and more compact table formatting.


Tutorial content is licensed under CC BY 4.0; code is licensed under the MIT License.