R: Evaluating Smoothing Spline ANOVA Estimate of Relative Risk

predict.sscox {gss} | R Documentation

## 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 components.

`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 a component `random=I(...)` in `newdata`, where the as-is function `I(...)` preserves the integrity of the Z matrix in data frame.

### Author(s)

Chong Gu, chong@stat.purdue.edu

### See Also

Fitting functions `sscox` and method `project.sscox`.

[Package gss version 2.1-7 Index]