Package: JMH
Type: Package
Title: Joint Model of Heterogeneous Repeated Measures and Survival Data
Version: 1.0.3
Date: 2024-02-19
Authors@R: c(
    person("Shanpeng", "Li", email = "lishanpeng0913@ucla.edu", 
        role = c("aut", "cre")),
    person("Jin", "Zhou", email = "jinjinzhou@g.ucla.edu", 
        role = "ctb"),       
    person("Hua", "Zhou", email = "huazhou@ucla.edu", 
        role = "ctb"),
    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) <arXiv:2301.06584>.
             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.
License: GPL (>= 3)
NeedsCompilation: yes
Imports: Rcpp (>= 1.0.7), parallel, dplyr, stats, caret, timeROC
LinkingTo: Rcpp, RcppEigen
Depends: R (>= 3.5.0), survival, nlme, utils, MASS, statmod
RoxygenNote: 7.2.3
Suggests: testthat (>= 3.0.0), spelling
Language: en-US
LazyData: true
Packaged: 2024-02-20 06:22:18 UTC; shanpengli
Author: Shanpeng Li [aut, cre],
  Jin Zhou [ctb],
  Hua Zhou [ctb],
  Gang Li [ctb]
Repository: CRAN
Date/Publication: 2024-02-20 06:40:02 UTC
Built: R 4.4.0; aarch64-apple-darwin20; 2024-04-07 06:33:44 UTC; unix
Archs: JMH.so.dSYM
