predict.survdnn {survdnn}R Documentation

Predict from a survdnn Model

Description

Generate predictions from a fitted 'survdnn' model for new data. Supports linear predictors, survival probabilities at specified time points, or cumulative risk estimates.

Usage

## S3 method for class 'survdnn'
predict(object, newdata, times = NULL, type = c("survival", "lp", "risk"), ...)

Arguments

object

An object of class '"survdnn"' returned by [survdnn()].

newdata

A data frame of new observations to predict on.

times

Numeric vector of time points at which to compute survival or risk probabilities. Required if 'type = "survival"' or 'type = "risk"'.

type

Character string specifying the type of prediction to return:

"lp"

Linear predictor (log-risk score; higher implies worse prognosis).

"survival"

Predicted survival probabilities at each value of 'times'.

"risk"

Cumulative risk (1 - survival) at a single time point.

...

Currently ignored (for future extensions).

Value

A numeric vector (if 'type = "lp"' or '"risk"'), or a data frame (if 'type = "survival"') with one row per observation and one column per 'times'.

Examples

library(survival)
data(veteran, package = "survival")

# Fit survdnn with Cox loss
mod <- survdnn(Surv(time, status) ~ age + karno + celltype, data = veteran,
               loss = "cox", epochs = 50, verbose = FALSE)

# Linear predictor (log-risk)
predict(mod, newdata = veteran, type = "lp")[1:5]

# Survival probabilities at selected times
predict(mod, newdata = veteran, type = "survival", times = c(30, 90, 180))[1:5, ]

# Cumulative risk at 180 days
predict(mod, newdata = veteran, type = "risk", times = 180)[1:5]

[Package survdnn version 0.6.0 Index]