mlstats: Multilevel Descriptive Statistics and Data Preparation

The mlstats package provides tools for multilevel descriptive statistics and data preparation (e.g., repeated measurements per person, or students nested within schools). It supports:

• Computing within-group and between-group correlations (within_between_correlations())

• Creating publication-ready descriptive statistics tables with ICCs and within-/between-group correlations (mldesc())

• Decomposing variables into within-group and between-group components for Random Effects Within-Between (REWB) models (decompose_within_between())

• Three estimation methods, selectable via the method argument of mldesc() and within_between_correlations(): variance decomposition (default), two-level structural equation modeling (via lavaan), and Bayesian multilevel modeling (via brms)

• Exporting result tables as 'gt' or 'tinytable' objects via print(result, format = "gt") or print(result, format = "tt")

See vignette("correlation-methods") for the statistical background, and media_diary for an example dataset.

See also

Useful links:

• https://felixdidi.github.io/mlstats/

• https://github.com/felixdidi/mlstats

• Report bugs at https://github.com/felixdidi/mlstats/issues

Author

Maintainer: Felix Dietrich mail@felix-dietrich.de [copyright holder]