Learning and Communicating Linear Mixed Models Without Data

Summarizes characteristics of linear mixed effects models without data or a fitted model by converting code for fitting lmer() from 'lme4' and lme() from 'nlme' into tables, equations, and visuals. Outputs can be used to learn how to fit linear mixed effects models in 'R' and to communicate about these models in presentations, manuscripts, and analysis plans.


LearnVizLMM

The objective of this package is to summarize characteristics of linear mixed effects models (LMMs) without data or a fitted model. Its functions convert code for fitting nlme::lme() and lme4::lmer() models into tables, equations, and visuals. These outputs can be used for learning how to fit LMMs in R and communicating about LMMs in presentations, manuscripts, and analysis plans.

Installation

# Install release version from CRAN
install.package("LearnVizLMM")

Tutorial

See the vignettes to learn how to use this package.

Reference manual

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install.packages("LearnVizLMM")

1.0.0 by Katherine Zavez, 2 years ago


https://github.com/kzavez/LearnVizLMM


Report a bug at https://github.com/kzavez/LearnVizLMM/issues


Browse source code at https://github.com/cran/LearnVizLMM


Authors: Katherine Zavez [aut, cre] , Ofer Harel [aut]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports cli, DiagrammeR, DiagrammeRsvg, dplyr, rsvg, stringr

Suggests kableExtra, knitr, rmarkdown, testthat


See at CRAN