Analysis of Event Data with Two Time Scales
Plot of the covariates' effects
Cumulative hazard over two time scales
Cumulative incidence surface over two time scales
Bin data on one time scale
Bin data on two time scales
Bin data on the Lexis diagram
Fit a smooth hazard model with one time scale
Numerical optimization of the 1ts model
Fit a smooth hazard model with two time scales
Numerical optimization of the 2ts model
Return the AIC of 1ts model
Return the AIC of 2ts model
Return the BIC of 1ts model
Return the BIC of 2ts model
Get estimated (log-)hazard values with 1 time scale
Get estimated (log-)hazard values with 1 time scale
Get estimated (log-)hazard surface with 2 time scales
Get estimated (log-)hazard surface with 2 time scales
Get the Hazard Ratios with their Standard Errors
Calculates AIC and BIC from object fitted via LMMsolver
Fit the 1d GLAM with covariates
Fit the 2d GLAM with covariates
Fit the 2d GLAM without covariates
Grid search for the optimal 1ts model
Grid search for the optimal 2ts model
Summary function for object of class 'haz2ts'
Summary function for object of class 'haz2tsLMM'
Image Plot of 2ts hazard
Image Plot of Standard Errors for the 2ts hazard
Iterative Weighted Least Squares algorithm for 1ts model
Construct bins over one or more time axes
Plot slices of the (log-) hazard
Plot method for a haz1ts object.
Plot method for a haz1ts object.
Plot method for a haz2ts object.
Plot method for a haz2tsLMM object.
Process data to fit model with LMMsolver
Prepare raw data by binning them in 1d or 2d
Print method for a data2ts object
Survival function with two time scales
Analyse time to event data with two time scales by estimating a smooth hazard that varies over two time scales and also, if covariates are available, to estimate a proportional hazards model with such a two-dimensional baseline hazard. Functions are provided to prepare the raw data for estimation, to estimate and to plot the two-dimensional smooth hazard. Extension to a competing risks model are implemented. For details about the method please refer to Carollo et al. (2024) <doi:10.1002/sim.10297>.
Useful links