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dyadMLM  

Tools for Dyadic Multilevel Models
View on CRAN: Click here


Download and install dyadMLM package within the R console
Install from CRAN:
install.packages("dyadMLM")

Install from Github:
library("remotes")
install_github("cran/dyadMLM")

Install by package version:
library("remotes")
install_version("dyadMLM", "0.2.0")



Attach the package and use:
library("dyadMLM")
Maintained by
Pascal Küng
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-30
Latest Update: 2026-07-30
Description:
Provides tools for dyadic multilevel modeling with linear and generalized linear mixed-effects models. It validates and prepares long-format cross-sectional and intensive longitudinal data, including ecological momentary assessment designs, for distinguishable and exchangeable dyads. It also supports datasets containing multiple observed dyad compositions. It constructs composition-aware, model-ready variables for Actor-Partner Interdependence Models (APIMs), Dyadic Score Models (DSMs), and Dyad-Individual Models (DIMs). Prepared data can be used with model engines such as 'glmmTMB' and 'brms' for Gaussian and non-Gaussian outcomes, including counts, proportions, and skewed continuous responses. Post-estimation tools compare compatible fitted models and back-transform exchangeable sum-and-difference random-effect covariance structures into member-level quantities. The APIM and DSM specifications and their relationships follow Iida et al. (2018) <doi:10.1177/0265407517725407>; the multilevel sum-and-difference random-effects implementation for exchangeable dyads adapts del Rosario and West (2025) <doi:10.1177/25152459251351286>.
How to cite:
Pascal Küng (2026). dyadMLM: Tools for Dyadic Multilevel Models. R package version 0.2.0, https://cran.r-project.org/web/packages/dyadMLM. Accessed 13 Oct. 2026.
Previous versions and publish date:
(2026-08-21 07:47), 0.1.0 (2026-07-30 19:20)
Other packages that cited dyadMLM R package
View dyadMLM citation profile
Other R packages that dyadMLM depends, imports, suggests or enhances
Complete documentation for dyadMLM
Functions, R codes and Examples using the dyadMLM R package
Full dyadMLM package functions and examples
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