survfit.lple: Compute a Survival Curve from a Local Linear Partial...

In statapps/lplb: Local Partial Likelihood Bootstrap (LPLB) test

Description

Computes the predicted survival function for a model fitted by (lple).

Usage

## S3 method for class 'lple'
## S3 method for class 'lple'
survfit(object, se.fit=TRUE, conf.int=.95)

Arguments

object	The results of a (lple) fit.
se.fit	A logical value indicating whether standard errors shall be computed. Default is TRUE.
conf.int	The level for a two-sided confidence interval on the survival curve. Default is 0.95.

Details

survfit.lple is called to compuate baseline survival function from the lple model lple.

The default method, survfit has its own help page. Use methods("survfit") to get all the methods for the survfit generic.

Value

survfit.lple returns a list of predicted baseline survival function, cumulative hazard function and residuals.

surv	Predicted baseline survival function when beta(w) = 0.
cumhaz	Baseline cumulative hazard function, -log(surv).
hazard	Baseline hazard function.
varhaz	Variance of the baseline hazard.
residuals	Martingale residuals of the (lple) model.
std.err	Standard error for the cumulative hazard function, if se.fit = TRUE.

See survfit for more detail about other output values such as upper, lower, conf.type. Confidence interval is based on log-transformation of survival function.

Author(s)

Bingshu E. Chen

See Also

The default method for survfit survfit, #survfit.lple

Examples

#
#  survfit(fit, se.fit = FALSE)
#

statapps/lplb documentation built on July 10, 2021, 6:14 p.m.