casebase
Fitting Flexible Smooth-in-Time Hazards and Risk Functions via Logistic and Multinomial Regression
Fit flexible and fully parametric hazard regression models to survival data with single event type or multiple competing causes via logistic and multinomial regression. Our formulation allows for arbitrary functional forms of time and its interactions with other predictors for time-dependent hazards and hazard ratios. From the fitted hazard model, we provide functions to readily calculate and plot cumulative incidence and survival curves for a given covariate profile. This approach accommodates any log-linear hazard function of prognostic time, treatment, and covariates, and readily allows for non-proportionality. We also provide a plot method for visualizing incidence density via population time plots. Based on the case-base sampling approach of Hanley and Miettinen (2009) doi:10.2202/1557-4679.1125, Saarela and Arjas (2015) doi:10.1111/sjos.12125, and Saarela (2015) doi:10.1007/s10985-015-9352-x.
- Version0.10.6
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- casebase citation info
- Last release08/17/2024
Documentation
- VignetteCompeting risk analysis
- VignetteCustomizing Population Time Plots
- VignettePlot Cumulative Incidence and Survival Curves
- VignettePlot Hazards and Hazard Ratios
- VignettePopulation Time Plots
- VignetteIntroduction to casebase sampling
- VignetteTime-Varying Covariates
- MaterialREADME
- MaterialNEWS
- In ViewsSurvival
Team
Sahir Bhatnagar
Maxime Turgeon
Show author detailsRolesAuthorOlli Saarela
Show author detailsRolesAuthorJames Hanley
Show author detailsRolesAuthorJesse Islam
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- Imports5 packages
- Suggests11 packages
- Reverse Suggests1 package