predict.sscox: Evaluating Smoothing Spline ANOVA Estimate of Relative Risk

In gss: General Smoothing Splines

Evaluating Smoothing Spline ANOVA Estimate of Relative Risk

Description

Evaluate terms in a smoothing spline ANOVA estimate of relative risk at arbitrary points. Standard errors of the terms can be requested for use in constructing Bayesian confidence intervals.

Usage

## S3 method for class 'sscox'
predict(object, newdata, se.fit=FALSE,
                        include=c(object$terms$labels,object$lab.p), ...)

Arguments

object	Object of class "sscox".
newdata	Data frame or model frame in which to predict.
se.fit	Flag indicating if standard errors are required.
include	List of model terms to be included in the prediction.
...	Ignored.

Value

For se.fit=FALSE, predict.sscox returns a vector of the evaluated relative risk.

For se.fit=TRUE, predict.sscox returns a list consisting of the following elements.

fit	Vector of evaluated relative risk.
se.fit	Vector of standard errors for log relative risk.

Note

For mixed-effect models through sscox, the Z matrix is set to 0 if not supplied. To supply the Z matrix, add an element random=I(...) in newdata, where the as-is function I(...) preserves the integrity of the Z matrix in data frame.

See Also

Fitting functions sscox and method project.sscox.

gss documentation built on Oct. 12, 2024, 1:08 a.m.