hzdrate.sshzd: Evaluating Smoothing Spline Hazard Estimates

In gss: General Smoothing Splines

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 "sshzd".
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.

gss documentation built on Aug. 16, 2023, 9:07 a.m.