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JMH
View on CRAN: Click
here
Download and install JMH package within the R console
Install from CRAN:
install.packages("JMH")
Install from Github:
library("remotes")
install_github("cran/JMH")
Install by package version:
library("remotes")
install_version("JMH", "1.0.3")
Attach the package and use:
library("JMH")
Maintained by
Shanpeng Li
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-06-15
Latest Update: 2024-02-20
Description:
Maximum likelihood estimation for the semi-parametric joint modeling of competing risks and longitudinal data in the presence of heterogeneous within-subject variability, proposed by Li and colleagues (2023) .
The proposed method models the within-subject variability of the biomarker and associates it with the risk of the competing risks event. The time-to-event data is modeled using a (cause-specific) Cox proportional hazards regression model with time-fixed covariates.
The longitudinal outcome is modeled using a mixed-effects location and scale model. The association is captured by shared random effects. The model
is estimated using an Expectation Maximization algorithm.
How to cite:
Shanpeng Li (2023). JMH: Joint Model of Heterogeneous Repeated Measures and Survival Data. R package version 1.0.3, https://cran.r-project.org/web/packages/JMH. Accessed 17 Feb. 2025.
Previous versions and publish date:
1.0.2 (2023-06-15 09:30)
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