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In cifmodeling: Visualization and Polytomous Modeling of Survival and Competing Risks
cifmodeling-package R Documentation
cifmodeling: Visualization and Polytomous Modeling of Survival and Competing Risks
Description
A publication-ready toolkit for modern survival and competing risks analysis with a minimal, formula-based interface. Both nonparametric estimation and direct polytomous regression of cumulative incidence functions (CIFs) are supported. The main functions 'cifcurve()', 'cifplot()', and 'cifpanel()' estimate survival and CIF curves and produce high-quality graphics with risk tables, censoring and competing-risk marks, and multi-panel or inset layouts built on 'ggplot2' and 'ggsurvfit'. The modeling function 'polyreg()' performs direct polytomous regression for coherent joint modeling of all cause-specific CIFs to estimate risk ratios, odds ratios, or subdistribution hazard ratios at user-specified time points. The function 'ciftest()' provides log-rank, Gray, robust score, augmented score, and multiple-direction tests for survival and competing-risk outcomes. All core functions adopt a formula-and-data syntax and return tidy and extensible outputs that integrate smoothly with 'modelsummary', 'broom', and the broader 'tidyverse' ecosystem. Key numerical routines are implemented in C++ via 'Rcpp'.
Author(s)
Maintainer: Shiro Tanaka gestimation@gmail.com (ORCID) [copyright holder]
Other contributors:
Shigetaka Kobari [contributor]
Chisato Honda [contributor]
See Also
Useful links:
cifmodeling documentation built on Nov. 11, 2026, 9:06 a.m.
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| cifmodeling-package | R Documentation |
cifmodeling: Visualization and Polytomous Modeling of Survival and Competing Risks
Description
A publication-ready toolkit for modern survival and competing risks analysis with a minimal, formula-based interface. Both nonparametric estimation and direct polytomous regression of cumulative incidence functions (CIFs) are supported. The main functions 'cifcurve()', 'cifplot()', and 'cifpanel()' estimate survival and CIF curves and produce high-quality graphics with risk tables, censoring and competing-risk marks, and multi-panel or inset layouts built on 'ggplot2' and 'ggsurvfit'. The modeling function 'polyreg()' performs direct polytomous regression for coherent joint modeling of all cause-specific CIFs to estimate risk ratios, odds ratios, or subdistribution hazard ratios at user-specified time points. The function 'ciftest()' provides log-rank, Gray, robust score, augmented score, and multiple-direction tests for survival and competing-risk outcomes. All core functions adopt a formula-and-data syntax and return tidy and extensible outputs that integrate smoothly with 'modelsummary', 'broom', and the broader 'tidyverse' ecosystem. Key numerical routines are implemented in C++ via 'Rcpp'.
Author(s)
Maintainer: Shiro Tanaka gestimation@gmail.com (ORCID) [copyright holder]
Other contributors:
Shigetaka Kobari [contributor]
Chisato Honda [contributor]
See Also
Useful links:
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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