lcra: Bayesian Joint Latent Class and Regression Models

For fitting Bayesian joint latent class and regression models using Gibbs sampling. See the documentation for the model. The technical details of the model implemented here are described in Elliott, Michael R., Zhao, Zhangchen, Mukherjee, Bhramar, Kanaya, Alka, Needham, Belinda L., "Methods to account for uncertainty in latent class assignments when using latent classes as predictors in regression models, with application to acculturation strategy measures" (2020) In press at Epidemiology <doi:10.1097/EDE.0000000000001139>.

Version:	1.1.2
Depends:	R (≥ 3.4.0)
Imports:	rlang, coda, rjags
Suggests:	R2WinBUGS, gtools
Published:	2020-08-07
Author:	Michael Elliot [aut], Zhangchen Zhao [aut], Michael Kleinsasser [aut, cre]
Maintainer:	Michael Kleinsasser <mkleinsa at umich.edu>
BugReports:	https://github.com/umich-biostatistics/lcra/issues
License:	GPL-2
URL:	https://github.com/umich-biostatistics/lcra
NeedsCompilation:	no
SystemRequirements:	JAGS 4.x.y or WinBUGS 1.4
Materials:	README
CRAN checks:	lcra results

Documentation:

Reference manual:

lcra.pdf

Downloads:

Package source:	lcra_1.1.2.tar.gz
Windows binaries:	r-devel: lcra_1.1.2.zip, r-release: lcra_1.1.2.zip, r-oldrel: lcra_1.1.2.zip
macOS binaries:	r-release (arm64): lcra_1.1.2.tgz, r-release (x86_64): lcra_1.1.2.tgz, r-oldrel: lcra_1.1.2.tgz

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