Package: FastJM
Type: Package
Title: Semi-Parametric Joint Modeling of Longitudinal and Survival Data
Version: 1.5.3
Date: 2025-11-08
Authors@R: c(
    person("Shanpeng", "Li", email = "lishanpeng0913@ucla.edu", 
        role = c("aut", "cre")),
    person("Ning", "Li", email = "liningpv@gmail.com", 
        role = "ctb"),
    person("Emily", "Ouyang", email = "eouya001@ucr.edu", 
        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>
Encoding: UTF-8
Description: A joint model for large-scale, competing risks time-to-event data with singular or multiple longitudinal biomarkers, implemented with the efficient algorithms developed by Li and colleagues (2022) <doi:10.1155/2022/1362913> and <doi:10.48550/arXiv.2506.12741>.
             The time-to-event data is modelled using a (cause-specific) Cox 
             proportional hazards regression model with time-fixed covariates. 
             The longitudinal biomarkers are modelled using a linear mixed 
             effects model. The association between the longitudinal submodel 
             and the survival submodel is captured through shared random 
             effects. It allows researchers to analyze large-scale data to 
             model biomarker trajectories, estimate their effects on event 
             outcomes, and dynamically predict future events from patients’ 
             past histories. A function for simulating survival and longitudinal 
             data for multiple biomarkers is also included alongside built-in 
             datasets.
License: GPL (>= 3)
NeedsCompilation: yes
Imports: Rcpp (>= 1.0.7), dplyr, nlme, caret, timeROC, future,
        future.apply, rlang (>= 0.4.11)
LinkingTo: Rcpp, RcppEigen
Depends: R (>= 3.5.0), survival, utils, MASS, statmod, magrittr
RoxygenNote: 7.3.2
LazyData: true
Packaged: 2025-11-08 08:55:02 UTC; shanpengli
Suggests: testthat (>= 3.0.0), spelling
Language: en-US
Config/testthat/edition: 3
Author: Shanpeng Li [aut, cre],
  Ning Li [ctb],
  Emily Ouyang [ctb],
  Hong Wang [ctb],
  Jin Zhou [ctb],
  Hua Zhou [ctb],
  Gang Li [ctb]
Repository: CRAN
Date/Publication: 2025-11-08 14:00:02 UTC
Built: R 4.4.3; x86_64-w64-mingw32; 2025-12-01 22:43:08 UTC; windows
Archs: x64
