predict.hdcox.model: Make Predictions from High-Dimensional Cox Models

Description Usage Arguments Value Examples

View source: R/01-hdnom-models.R

Description

Predict overall survival probability at certain time points from established Cox models.

Usage

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## S3 method for class 'hdcox.model'
predict(object, x, y, newx, pred.at, ...)

Arguments

object

Model object fitted by hdcox.*() functions.

x

Data matrix used to fit the model.

y

Response matrix made with Surv.

newx

Matrix (with named columns) of new values for x at which predictions are to be made.

pred.at

Time point at which prediction should take place.

...

Other parameters (not used).

Value

A nrow(newx) x length(pred.at) matrix containing overall survival probablity.

Examples

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library("survival")

# Load imputed SMART data
data("smart")
x = as.matrix(smart[, -c(1, 2)])
time = smart$TEVENT
event = smart$EVENT
y = Surv(time, event)

fit = hdcox.lasso(x, y, nfolds = 5, rule = "lambda.1se", seed = 11)
predict(fit, x, y, newx = x[101:105, ], pred.at = 1:10 * 365)

road2stat/hdnom documentation built on Nov. 13, 2018, 9:06 a.m.