Package: lcra 1.1.5

Michael Kleinsasser

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>.

Authors:Michael Elliot [aut], Zhangchen Zhao [aut], Michael Kleinsasser [aut, cre]

lcra_1.1.5.tar.gz
lcra_1.1.5.tar.gz(r-4.5-noble)lcra_1.1.5.tar.gz(r-4.4-noble)
lcra_1.1.5.tgz(r-4.4-emscripten)lcra_1.1.5.tgz(r-4.3-emscripten)
lcra.pdf |lcra.html
lcra/json (API)

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

Peer review:

Bug tracker:https://github.com/umich-biostatistics/lcra/issues

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:

1.70 score 2 scripts 188 downloads 1 exports 4 dependencies

Last updated 9 months agofrom:2ba5afa517. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-linuxOKNov 04 2024

Exports:lcra

Dependencies:codalatticerjagsrlang