Package: FastJM
Type: Package
Title: Semi-Parametric Joint Modeling of Longitudinal and Survival Data
Version: 1.1.2
Date: 2022-02-15
Authors@R: c(
    person("Shanpeng", "Li", email = "lishanpeng0913@ucla.edu", 
        role = c("aut", "cre")),
    person("Ning", "Li", email = "liningpv@gmail.com", 
        role = "ctb"),
    person("Hong", "Wang", email = "wh@csu.edu.cn", 
        role = "ctb"),
    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 
    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.
License: GPL (>= 3)
NeedsCompilation: yes
Imports: Rcpp (>= 1.0.7), survival, dplyr, nlme, mvtnorm
LinkingTo: Rcpp, RcppEigen
Depends: R (>= 3.5.0), MASS, statmod
RoxygenNote: 7.1.2
LazyData: true
Packaged: 2022-02-15 16:30:26 UTC; shanpengli
Suggests: testthat (>= 3.0.0), spelling
Language: en-US
Config/testthat/edition: 3
Author: Shanpeng Li [aut, cre],
  Ning Li [ctb],
  Hong Wang [ctb],
  Jin Zhou [ctb],
  Hua Zhou [ctb],
  Gang Li [ctb]
Repository: CRAN
Date/Publication: 2022-02-16 17:00:06 UTC
