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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.
| Version: | 1.4.2 |
| Depends: | R (≥ 3.5.0), statmod, MASS |
| Imports: | Rcpp (≥ 1.0.7), dplyr, nlme, caret, survival, timeROC |
| LinkingTo: | Rcpp, RcppEigen |
| Suggests: | testthat (≥ 3.0.0), spelling |
| Published: | 2024-03-01 |
| Author: | Shanpeng Li [aut, cre], Ning Li [ctb], Hong Wang [ctb], 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 NEWS |
| CRAN checks: | FastJM results |
| Reference manual: | FastJM.pdf |
| Package source: | FastJM_1.4.2.tar.gz |
| Windows binaries: | r-devel: FastJM_1.4.2.zip, r-release: FastJM_1.4.2.zip, r-oldrel: FastJM_1.4.2.zip |
| macOS binaries: | r-release (arm64): FastJM_1.4.2.tgz, r-oldrel (arm64): FastJM_1.4.2.tgz, r-release (x86_64): FastJM_1.4.2.tgz, r-oldrel (x86_64): FastJM_1.4.2.tgz |
| Old sources: | FastJM archive |
| Reverse imports: | jmBIG |
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