binaryMM: Flexible Marginalized Models for Binary Correlated Outcomes

Estimates marginalized mean and dependence model parameters for correlated binary response data. Dependence model may include transition and/or latent variable terms. Methods are described in: Heagerty (1999) <doi:10.1111/j.0006-341x.1999.00688.x>, Heagerty (2002) <doi:10.1111/j.0006-341x.2002.00342.x>, Schildcrout and Heagerty (2007) <doi:10.1111/j.1541-0420.2006.00680.x>.

Version: 0.1.0
Imports: fastGHQuad, MASS, Rcpp
Suggests: rmarkdown, knitr, testthat (≥ 3.0.0)
Published: 2022-09-21
Author: Jonathan Schildcrout [aut], Nathaniel Mercaldo [aut], Chiara Di Gravio [cre]
Maintainer: Chiara Di Gravio <chiara.di.gravio at vanderbilt.edu>
License: MIT + file LICENSE
NeedsCompilation: yes
Materials: README
CRAN checks: binaryMM results

Documentation:

Reference manual: binaryMM.pdf
Vignettes: binaryMM: Fitting Flexible Marginalized Models for Binary Correlated Outcomes

Downloads:

Package source: binaryMM_0.1.0.tar.gz
Windows binaries: r-devel: binaryMM_0.1.0.zip, r-release: binaryMM_0.1.0.zip, r-oldrel: binaryMM_0.1.0.zip
macOS binaries: r-release (arm64): binaryMM_0.1.0.tgz, r-oldrel (arm64): binaryMM_0.1.0.tgz, r-release (x86_64): binaryMM_0.1.0.tgz, r-oldrel (x86_64): binaryMM_0.1.0.tgz

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