The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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.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.
| Version: | 1.0.3 |
| Depends: | R (≥ 3.5.0), survival, nlme, utils, MASS, statmod |
| Imports: | Rcpp (≥ 1.0.7), parallel, dplyr, stats, caret, timeROC |
| LinkingTo: | Rcpp, RcppEigen |
| Suggests: | testthat (≥ 3.0.0), spelling |
| Published: | 2024-02-20 |
| Author: | Shanpeng Li [aut, cre], Jin Zhou [ctb], Hua Zhou [ctb], Gang Li [ctb] |
| Maintainer: | Shanpeng Li <lishanpeng0913 at ucla.edu> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| Language: | en-US |
| Materials: | README |
| CRAN checks: | JMH results |
| Reference manual: | JMH.pdf |
| Package source: | JMH_1.0.3.tar.gz |
| Windows binaries: | r-devel: JMH_1.0.3.zip, r-release: JMH_1.0.3.zip, r-oldrel: JMH_1.0.3.zip |
| macOS binaries: | r-release (arm64): JMH_1.0.3.tgz, r-oldrel (arm64): JMH_1.0.3.tgz, r-release (x86_64): JMH_1.0.3.tgz, r-oldrel (x86_64): JMH_1.0.3.tgz |
| Old sources: | JMH archive |
Please use the canonical form https://CRAN.R-project.org/package=JMH to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.