predict.survreg {survival}R Documentation

Predicted Values for a 'survreg' Object

Description

Predicted values for a survreg object

Usage

## S3 method for class 'survreg':
predict(object, newdata, 
type=c("response", "link", "lp", "linear",  "terms", "quantile", 
        "uquantile"), 
se.fit=FALSE, terms=NULL, p=c(0.1, 0.9),...)

Arguments

object result of a model fit using the survreg function.
newdata data for prediction. If absent, predictions are for the subjects used in the original fit.
type the type of predicted value. This can be on the original scale of the data (response), the linear predictor ("linear", with "lp" as an allowed abbreviation), a predicted quantile on the original scale of the data ("quantile"), a quantile on the linear predictor scale ("uquantile"), or the matrix of terms for the linear predictor ("terms"). At this time "link" and linear predictor ("lp") are identical.
se.fit if TRUE, include the standard errors of the prediction in the result.
terms subset of terms. The default for residual type "terms" is a matrix with one column for every term (excluding the intercept) in the model.
p vector of percentiles. This is used only for quantile predictions.
... other arguments

Value

a vector or matrix of predicted values.

References

Escobar and Meeker (1992). Assessing influence in regression analysis with censored data. Biometrics, 48, 507-528.

See Also

survreg, residuals.survreg

Examples

# Draw figure 1 from Escobar and Meeker
fit <- survreg(Surv(time,status) ~ age + age^2, data=stanford2,
        dist='lognormal')
plot(stanford2$age, stanford2$time, xlab='Age', ylab='Days',
        xlim=c(0,65), ylim=c(.01, 10^6), log='y')
pred <- predict(fit, newdata=list(age=1:65), type='quantile',
                 p=c(.1, .5, .9))
matlines(1:65, pred, lty=c(2,1,2), col=1)

[Package survival version 2.17 Index]