Fitting Flexible Smooth-in-Time Hazards and Risk Functions via Logistic and Multinomial Regression
Compute absolute risks using the fitted hazard function.
Check that Event is in Correct Format
An S4 class to store the output of fitSmoothHazard
Compute confidence intervals for risks
Fit smooth-in-time parametric hazard functions.
Plot Fitted Hazard Curve as a Function of Time
Plot Hazards and Hazard Ratios
Population Time Plot
Create case-base dataset for use in fitting parametric hazard function...
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>.