Package 'CoxRMSTSimpson'

Calculate RMST from a Cox Model

Description

Predicts survival curves for supplied covariate profiles and calculates their RMST using Simpson's rule.

Usage

cox_rmst(fit, newdata, tau, n_grid = 101)

Arguments

fit	A fitted survival::coxph model.
newdata	Data frame of covariate profiles. Each row defines one survival curve.
tau	Positive restriction time.
n_grid	Odd number of equally spaced grid points.

Value

An object of class "cox_rmst" containing survival curves, RMST estimates, the fitted model, and the time grid.

Examples

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

fit <- coxph(Surv(time, status == 2) ~ age + sex, data = lung)

profiles <- data.frame(
  age = c(50, 70),
  sex = c(1, 2),
  row.names = c("Younger", "Older")
)

result <- cox_rmst(fit, newdata = profiles, tau = 365)
print(result)

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Plot Cox Survival Curves with Shaded RMST Areas

Description

Plot Cox Survival Curves with Shaded RMST Areas

Usage

plot_cox_rmst(x, colors = NULL, alpha = 0.2, legend_position = "topright", ...)

Arguments

x	An object returned by cox_rmst().
colors	Colors for the survival curves.
alpha	Transparency for shaded areas, between 0 and 1.
legend_position	Position passed to graphics::legend().
...	Additional arguments reserved for future methods.

Value

Invisibly returns x.

Examples

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

fit <- coxph(Surv(time, status == 2) ~ age + sex, data = lung)

profiles <- data.frame(
  age = c(50, 70),
  sex = c(1, 2),
  row.names = c("Younger", "Older")
)

result <- cox_rmst(fit, newdata = profiles, tau = 365)
plot_cox_rmst(result)

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Integrate a Survival Curve Using Simpson's Rule

Description

Calculates the area under a survival curve using composite Simpson's 1/3 rule.

Usage

simpson_rmst(t, S)

Arguments

t	Equally spaced, increasing time points.
S	Survival probabilities corresponding to t.

Value

A numeric scalar representing the integrated area.

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Simulate Survival Data Under a Proportional Hazards Model

Description

Simulate Survival Data Under a Proportional Hazards Model

Usage

simulate_survival_data(
  n = 200,
  beta = 0.7,
  lambda = 0.03,
  censor_rate = 0.005,
  seed = NULL
)

Arguments

n	Number of subjects.
beta	True regression coefficient for X.
lambda	Baseline exponential hazard rate.
censor_rate	Independent exponential censoring rate.
seed	Optional random seed.

Value

A data frame with time, status, and X.

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