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longit  

High Dimensional Longitudinal Data Analysis Using MCMC
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("longit", "0.1.0")



Attach the package and use:
library("longit")
Maintained by
Atanu Bhattacharjee
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-04-15
Latest Update: 2021-04-15
Description:
High dimensional longitudinal data analysis with Markov Chain Monte Carlo(MCMC). Currently support mixed effect regression with or without missing observations by considering covariance structures. It provides estimates by missing at random and missing not at random assumptions. In this R package, we present Bayesian approaches that statisticians and clinical researchers can easily use. The functions' methodology is based on the book "Bayesian Approaches in Oncology Using R and OpenBUGS" by Bhattacharjee A (2020) .
How to cite:
Atanu Bhattacharjee (2021). longit: High Dimensional Longitudinal Data Analysis Using MCMC. R package version 0.1.0, https://cran.r-project.org/web/packages/longit. Accessed 28 Oct. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited longit R package
View longit citation profile
Other R packages that longit depends, imports, suggests or enhances
Complete documentation for longit
Functions, R codes and Examples using the longit R package
Some associated functions: Bysmixed . BysmxDIC . BysmxHPD . Bysmxms . Bysmxmss . creg . gh . hdmarjg . hdmnarjg . longitdata . msrep . mvncovar1 . mvncovar2 . repdata . 
Some associated R codes: Bysmixed.R . BysmxDIC.R . BysmxHPD.R . Bysmxms.R . Bysmxmss.R . creg.R . gh.R . hdmarjg.R . hdmnarjg.R . longitdata.R . msrep.R . mvncovar1.R . mvncovar2.R . repdata.R .  Full longit package functions and examples
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