kmsurv: Kaplan-Meier Survival Probability Based on Pooled Sample

In lrstat: Power and Sample Size Calculation for Non-Proportional Hazards and Beyond

Kaplan-Meier Survival Probability Based on Pooled Sample

Description

Obtains the limit of Kaplan-Meier estimate of the survival probabilities based on the pooled sample.

Usage

kmsurv(
  time = NA_real_,
  allocationRatioPlanned = 1,
  piecewiseSurvivalTime = 0L,
  lambda1 = NA_real_,
  lambda2 = NA_real_,
  gamma1 = 0L,
  gamma2 = 0L
)

Arguments

time	A vector of analysis times at which to calculate the Kaplan-Meier Survival Probability.
allocationRatioPlanned	Allocation ratio for the active treatment versus control. Defaults to 1 for equal randomization.
piecewiseSurvivalTime	A vector that specifies the starting time of piecewise exponential survival time intervals. Must start with 0, e.g., c(0, 6) breaks the time axis into 2 event intervals: [0, 6) and [6, Inf). Defaults to 0 for exponential distribution.
lambda1	A vector of hazard rates for the event for the active treatment group. One for each analysis time interval.
lambda2	A vector of hazard rates for the event for the control group. One for each analysis time interval.
gamma1	The hazard rate for exponential dropout, or a vector of hazard rates for piecewise exponential dropout for the active treatment group.
gamma2	The hazard rate for exponential dropout, or a vector of hazard rates for piecewise exponential dropout for the control group.

Value

A vector of Kaplan-Meier survival probabilities at the specified analysis times for piecewise exponential survival and dropout distributions.

Author(s)

Kaifeng Lu, [e-mail]

Examples

# Piecewise exponential survivals, and 5% dropout by the end of
# 1 year.

kmsurv(t = c(2, 8), allocationRatioPlanned = 1,
       piecewiseSurvivalTime = c(0, 6),
       lambda1 = c(0.0533, 0.0309), lambda2 = c(0.0533, 0.0533),
       gamma1 = -log(1-0.05)/12, gamma2 = -log(1-0.05)/12)

lrstat documentation built on April 4, 2025, 2:24 a.m.