Package: JMH
Type: Package
Title: Joint Model of Heterogeneous Repeated Measures and Survival Data
Version: 1.0.4
Date: 2026-03-29
Authors@R: c(
    person("Shanpeng", "Li", email = "lishanpeng0913@ucla.edu", 
        role = c("aut", "cre")),
    person("Gang", "Li", email = "vli@ucla.edu", 
        role = "ctb")
    )
Maintainer: Shanpeng Li <lishanpeng0913@ucla.edu>
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) <doi:10.48550/arXiv.2506.12741>.
             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. This is the final release of the 'JMH' package. Active development has been moved to the 'FastJM' package, which provides improved functionality and ongoing support. Users are strongly encouraged to transition to 'FastJM'.
License: GPL (>= 3)
NeedsCompilation: yes
Imports: Rcpp (>= 1.0.7), parallel, dplyr, stats, caret, pec
LinkingTo: Rcpp, RcppEigen
Depends: R (>= 3.5.0), survival, nlme, utils, MASS, statmod, magrittr
RoxygenNote: 7.3.2
Suggests: testthat (>= 3.0.0), spelling
Language: en-US
LazyData: true
Encoding: UTF-8
Packaged: 2026-04-02 05:23:12 UTC; shanpengli
Author: Shanpeng Li [aut, cre],
  Gang Li [ctb]
Repository: CRAN
Date/Publication: 2026-04-02 15:50:02 UTC
Built: R 4.6.0; x86_64-w64-mingw32; 2026-05-04 04:26:17 UTC; windows
Archs: x64
