CRAN/E | FastJM

FastJM

Semi-Parametric Joint Modeling of Longitudinal and Survival Data

Installation

About

Maximum likelihood estimation for the semi-parametric joint modeling of competing risks and longitudinal data applying customized linear scan algorithms, proposed by Li and colleagues (2022) doi:10.1155/2022/1362913. The time-to-event data is modelled using a (cause-specific) Cox proportional hazards regression model with time-fixed covariates. The longitudinal outcome is modelled using a linear mixed effects model. The association is captured by shared random effects. The model is estimated using an Expectation Maximization algorithm.

Key Metrics

Version 1.4.2
R ≥ 3.5.0
Published 2024-03-01 59 days ago
Needs compilation? yes
License GPL (≥ 3)
CRAN checks FastJM results
Language en-US

Downloads

Yesterday 7 0%
Last 7 days 67 -11%
Last 30 days 255 -40%
Last 90 days 980 -14%
Last 365 days 3.676 -5%

Maintainer

Maintainer

Shanpeng Li

lishanpeng0913@ucla.edu

Authors

Shanpeng Li

aut / cre

Ning Li

ctb

Hong Wang

ctb

Jin Zhou

ctb

Hua Zhou

ctb

Gang Li

ctb

Material

README
NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

FastJM archive

Depends

R ≥ 3.5.0
statmod
MASS

Imports

Rcpp ≥ 1.0.7
dplyr
nlme
caret
survival
timeROC

Suggests

testthat ≥ 3.0.0
spelling

LinkingTo

Rcpp
RcppEigen

Reverse Imports

jmBIG