# ------------------------------------------------
# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# ------------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "BJM" in publications use:'
type: software
license: MIT
title: 'BJM: Backward Joint Model for the Dynamic Prediction of Both Time-to-Event
  and Longitudinal Outcomes'
version: 0.1.0
abstract: Provides tools to fit joint models of multivariate longitudinal data and
  time-to-event data for dynamic prediction. It allows the joint prediction of both
  future time-to-event outcomes and future longitudinal outcomes conditional on survival.
  The models accommodate irregularly measured longitudinal data and competing risks
  outcomes. The use of the backward joint model enables fast and efficient computation,
  especially for applications with large sample sizes and many longitudinal variables.
authors:
- family-names: Li
  given-names: Wenhao
  email: wenhaoli.jlu@gmail.com
- family-names: Li
  given-names: Liang
  email: LLi15@mdanderson.org
repository: https://cran.r-universe.dev
commit: d5c44f3c6ca7c4580914fd5958ac6b6998f4fca0
date-released: '2026-07-04'
contact:
- family-names: Li
  given-names: Wenhao
  email: wenhaoli.jlu@gmail.com