| hzdrate.sshzd {gss} | R Documentation |
Evaluating Smoothing Spline Hazard Estimates
Description
Evaluate smoothing spline hazard estimates by sshzd.
Usage
hzdrate.sshzd(object, x, se=FALSE, include=c(object$terms$labels,object$lab.p))
hzdcurve.sshzd(object, time, covariates=NULL, se=FALSE)
survexp.sshzd(object, time, covariates=NULL, start=0)
Arguments
object |
Object of class |
x |
Data frame or vector of points on which hazard is to be evaluated. |
se |
Flag indicating if standard errors are required. |
include |
List of model terms to be included in the evaluation. |
time |
Vector of time points. |
covariates |
Vector of covariate values. |
start |
Optional starting times of the intervals. |
Value
For se=FALSE, hzdrate.sshzd returns a vector of hazard
evaluations, and hzdcurve.sshzd returns a vector or columns of
hazard curve(s) evaluated on time points at the
covariates values. For se=TRUE, hzdrate.sshzd
and hzdcurve.sshzd return a list consisting of the following
elements.
fit |
Vector or columns of hazard. |
se.fit |
Vector or columns of standard errors for log hazard. |
survexp.sshzd returns a vector or columns of expected
survivals based on the cumulative hazards over (start,
time) at the covariates values, which in fact are the
(conditional) survival probabilities S(time)/S(start).
Note
For left-truncated data, start must be at or after the
earliest truncation point.
See Also
Fitting function sshzd.