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
Config/pak/sysreqs: cmake make libicu-dev libuv1-dev
Repository: https://shanpengli.r-universe.dev
Date/Publication: 2026-04-02 05:22:23 UTC
RemoteUrl: https://github.com/shanpengli/jmh
RemoteRef: HEAD
RemoteSha: 7a69edb461f6b085194e03e69469c1a9486e935b
Packaged: 2026-07-05 06:30:02 UTC; root
Author: Shanpeng Li [aut, cre],
  Gang Li [ctb]