Package 'survC'

Compute risk scores from a fitted survival model

Description

This helper wraps stats::predict() for coxph objects so that package users can easily obtain linear predictors (default) or risk scores to feed into downstream metrics such as time-dependent ROC or Harrell's C-index.

Usage

calc_risk_score(model, data = NULL, type = "lp", ...)

Arguments

model	A fitted coxph object.
data	Optional dataset on which to score the model. Defaults to the training data stored within model.
type	Scale of the predictions to return. Either "lp" (linear predictor, the default) or "risk". If NULL or omitted, "lp" is used.
...	Additional arguments passed to stats::predict().

Value

A numeric vector containing the requested risk scores.

Examples

if (requireNamespace("survival", quietly = TRUE)) {
  fit <- survival::coxph(survival::Surv(time, status) ~ age, data = survival::lung)
  # Linear predictor on the training data
  calc_risk_score(fit)

  # Risk scale predictions on new data
  calc_risk_score(fit, survival::lung, type = "risk")
}

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Calculate Harrell's C-index with 95% CI

Description

Calculate Harrell's C-index with 95% CI

Usage

cindex_calc(model, newdata = NULL, digits = 3)

Arguments

model	a 'coxph' object
newdata	optional validation dataset
digits	number of decimal places for rounding (default 3).

Value

numeric vector of C-index (lower, upper)

Examples

library(survival)
fit <- coxph(Surv(time, status) ~ age + sex, data = lung)
cindex_calc(fit)

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Calculate time-dependent ROC and AUC

Description

Calculate time-dependent ROC and AUC

Usage

tdroc_calc(time, status, marker, times)

Arguments

time	Survival time vector
status	Event indicator (1 = event, 0 = censor)
marker	Risk score or linear predictor
times	Vector of time points (e.g., c(365, 730, 1095))

Value

A data.frame with AUCs for each time

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Generate survival model validation report

Description

Generate survival model validation report

Usage

validation_report(
  train_data,
  val_data,
  model,
  time_col,
  status_col,
  times = c(365, 730, 1095),
  time_unit = "days",
  output = "validation_report.pptx"
)

Arguments

train_data	training dataset containing survival outcomes.
val_data	validation dataset containing survival outcomes.
model	fitted 'coxph'
time_col	name of the survival time column present in both datasets
status_col	name of the event indicator column present in both datasets
times	follow-up timepoints
time_unit	character label for the time axis (default = "days")
output	file path (.pptx or .html)

Value

Writes validation report

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