dyadMLM: Tools for Dyadic Multilevel Models

dyadMLM validates and prepares cross-sectional and intensive longitudinal dyadic data for multilevel modeling. It creates model-ready variables for APIMs, DIMs, and DSMs and provides supporting post-estimation tools.

Main functions

• prepare_dyad_data() validates long-format dyadic data and creates model-ready variables.

• compare_nested_models() compares compatible nested glmmTMB models fitted to equivalent data.

• recover_exchangeable_covariance() back-transforms exchangeable shared/difference random-effect covariance structures into member-level quantities.

Example data

See dyads_cross and dyads_ild for Gaussian examples, and dyads_nbinom_cross and dyads_nbinom_ild for negative-binomial examples.

Getting started

See vignette("getting-started", package = "dyadMLM") for an overview. The APIM, DIM, and DSM vignettes provide model-specific examples.

See also

Useful links:

• https://pascal-kueng.github.io/dyadMLM/

• https://github.com/Pascal-Kueng/dyadMLM

• Report bugs at https://github.com/Pascal-Kueng/dyadMLM/issues

Author

Maintainer: Pascal Küng kueng.pascal@gmail.com (ORCID) [copyright holder]

Authors:

• Pascal Küng kueng.pascal@gmail.com (ORCID) [copyright holder]