Package: Mmcsd 1.0.0

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>.

Authors:Pedro Pacheco [aut, cre], Marcel Vieira [aut], Gustavo Silva [aut]

Mmcsd_1.0.0.tar.gz
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Mmcsd.pdf |Mmcsd.html
Mmcsd/json (API)
NEWS

# Install 'Mmcsd' in R:
install.packages('Mmcsd', repos = c('https://gustavo039.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.70 score 3 scripts 246 downloads 4 exports 30 dependencies

Last updated 2 years agofrom:facc01c8d7. Checks:1 OK, 7 WARNING. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 19 2025
R-4.5-winWARNINGFeb 19 2025
R-4.5-macWARNINGFeb 19 2025
R-4.5-linuxWARNINGFeb 19 2025
R-4.4-winWARNINGFeb 19 2025
R-4.4-macWARNINGFeb 19 2025
R-4.3-winWARNINGFeb 19 2025
R-4.3-macWARNINGFeb 19 2025

Exports:%>%cov_mmcsdmmcsdsigmaThetaExpr_viewer

Dependencies:clicpp11data.tabledplyrevaluatefansigenericsgluehighrjsonliteknitrlifecyclemagrittrpillarpkgconfigpurrrR6rlangrliststringistringrtibbletidyrtidyselectutf8vctrswithrxfunXMLyaml

Modeling complex longitudinal data in a quick and easy way

Rendered frommy-vignette.Rmdusingknitr::rmarkdownon Feb 19 2025.

Last update: 2023-03-31
Started: 2023-03-31