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:
lcra_1.1.5.tar.gz
lcra_1.1.5.zip(r-4.5)lcra_1.1.5.zip(r-4.4)lcra_1.1.5.zip(r-4.3)
lcra_1.1.5.tgz(r-4.4-any)lcra_1.1.5.tgz(r-4.3-any)
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://umich-biostatistics.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/umich-biostatistics/lcra/issues
- express - Small simulated data set
- latent3 - Simulated data set number 2
- latent3_binary - Simulated data set number 2
- paper_sim - Simulated data set
- paper_sim_binary - Simulated data set
Last updated 9 months agofrom:6bd299a67e. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 14 2024 |
| R-4.5-win | OK | Nov 14 2024 |
| R-4.5-linux | OK | Nov 14 2024 |
| R-4.4-win | OK | Nov 14 2024 |
| R-4.4-mac | OK | Nov 14 2024 |
| R-4.3-win | OK | Nov 14 2024 |
| R-4.3-mac | OK | Nov 14 2024 |
Exports:lcra
