| predict.sscox {gss} | R Documentation |
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.
## S3 method for class 'sscox'
predict(object, newdata, se.fit=FALSE,
include=c(object$terms$labels,object$lab.p), ...)
object |
Object of class |
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. |
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 components.
fit |
Vector of evaluated relative risk. |
se.fit |
Vector of standard errors for log relative risk. |
For mixed-effect models through sscox, the Z matrix is
set to 0 if not supplied. To supply the Z matrix, add a component
random=I(...) in newdata, where the as-is function
I(...) preserves the integrity of the Z matrix in data
frame.
Chong Gu, chong@stat.purdue.edu
Fitting functions sscox and method
project.sscox.