Mmcsd: Modeling Complex Longitudinal Data in a Quick and Easy Way

Matching longitudinal methodology models with complex sampling design. It fits fixed and random effects models and covariance structured models so far. It also provides tools to perform statistical tests considering these specifications as described in : Pacheco, P. H. (2021). "Modeling complex longitudinal data in R: development of a statistical package." <https://repositorio.ufjf.br/jspui/bitstream/ufjf/13437/1/pedrohenriquedemesquitapacheco.pdf>.

Version: 1.0.0
Depends: R (≥ 2.10)
Imports: dplyr, knitr, magrittr, methods, purrr, rlist, stats, tibble, tidyr
Suggests: rmarkdown, simstudy, kableExtra, tidyverse
Published: 2023-03-31
Author: Pedro Pacheco ORCID iD [aut, cre], Marcel Vieira ORCID iD [aut], Gustavo Silva [aut]
Maintainer: Pedro Pacheco <gustavoaeida2002 at gmail.com>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
CRAN checks: Mmcsd results

Documentation:

Reference manual: Mmcsd.pdf
Vignettes: Modeling complex longitudinal data in a quick and easy way

Downloads:

Package source: Mmcsd_1.0.0.tar.gz
Windows binaries: r-devel: Mmcsd_1.0.0.zip, r-release: Mmcsd_1.0.0.zip, r-oldrel: Mmcsd_1.0.0.zip
macOS binaries: r-release (arm64): Mmcsd_1.0.0.tgz, r-oldrel (arm64): Mmcsd_1.0.0.tgz, r-release (x86_64): Mmcsd_1.0.0.tgz

Linking:

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