Package: multilevelcoda
Title: Estimate Bayesian Multilevel Models for Compositional Data
Version: 1.0.0
Authors@R: 
    c(person(given = "Flora",
             family = "Le",
             role = c("aut", "cre"),
             email = "13florale@gmail.com",
             comment = c(ORCID = "0000-0003-0089-8167")),
      person(given = "Joshua F.",
             family = "Wiley",
             role = c("aut"),
             email = "jwiley.psych@gmail.com",
             comment = c(ORCID = "0000-0002-0271-6702")))
URL: https://florale.github.io/multilevelcoda/,
        https://github.com/florale/multilevelcoda
BugReports: https://github.com/florale/multilevelcoda/issues
Description: Implement Bayesian Multilevel Modelling for compositional data 
             in a multilevel framework. Compute multilevel compositional data and 
             Isometric log ratio (ILR) at between and within-person levels, 
             fit Bayesian multilevel models for compositional predictors and outcomes, 
             and run post-hoc analyses such as isotemporal substitution models.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.1
Depends: R (>= 4.0.0)
Imports: stats, data.table (>= 1.12.0), compositions, zCompositions,
        bayestestR, brms, extraoperators, ggplot2, emmeans, insight,
        ggsci, foreach
Suggests: testthat (>= 3.0.0), covr, withr, knitr, rmarkdown, doFuture,
        lme4
Config/testthat/edition: 3
Config/testthat/parallel: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2023-01-13 00:09:26 UTC; florale
Author: Flora Le [aut, cre] (<https://orcid.org/0000-0003-0089-8167>),
  Joshua F. Wiley [aut] (<https://orcid.org/0000-0002-0271-6702>)
Maintainer: Flora Le <13florale@gmail.com>
Repository: CRAN
Date/Publication: 2023-01-13 19:10:02 UTC
Built: R 4.1.1; ; 2023-01-13 19:23:02 UTC; unix
