survfit.lple {lpl}R Documentation

Compute a Survival Curve from a Local Linear Partial Likelihood Estimate.

Description

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

Usage

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

Arguments

formula

a fitted model from (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

...

other arguments to the specific method

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

#
# See example in lple
#

[Package lpl version 0.11 Index]