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lcra  

Bayesian Joint Latent Class and Regression Models
View on CRAN: Click here


Download and install lcra package within the R console
Install from CRAN:
install.packages("lcra")

Install from Github:
library("remotes")
install_github("cran/lcra")

Install by package version:
library("remotes")
install_version("lcra", "1.1.5")



Attach the package and use:
library("lcra")
Maintained by
Michael Kleinsasser
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-08-07
Latest Update: 2020-08-07
Description:
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 .
How to cite:
Michael Kleinsasser (2020). lcra: Bayesian Joint Latent Class and Regression Models. R package version 1.1.5, https://cran.r-project.org/web/packages/lcra. Accessed 06 Nov. 2024.
Previous versions and publish date:
1.1.2 (2020-08-07 15:50)
Other packages that cited lcra R package
View lcra citation profile
Other R packages that lcra depends, imports, suggests or enhances
Complete documentation for lcra
Functions, R codes and Examples using the lcra R package
Some associated functions: express . latent3 . latent3_binary . lcra . paper_sim . paper_sim_binary . 
Some associated R codes: WinBUGS.R . data.R . lcra.R . write_model.R .  Full lcra package functions and examples
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