rmstat: Stratified difference in restricted mean survival times

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

Stratified difference in restricted mean survival times

Description

Obtains the stratified restricted mean survival times and difference in restricted mean survival times at given calendar times.

Usage

rmstat(
  time = NA_real_,
  milestone = NA_real_,
  allocationRatioPlanned = 1,
  accrualTime = 0L,
  accrualIntensity = NA_real_,
  piecewiseSurvivalTime = 0L,
  stratumFraction = 1L,
  lambda1 = NA_real_,
  lambda2 = NA_real_,
  gamma1 = 0L,
  gamma2 = 0L,
  accrualDuration = NA_real_,
  followupTime = NA_real_,
  fixedFollowup = 0L
)

Arguments

time	A vector of calendar times at which to calculate the restricted mean survival time.
milestone	The milestone time at which to calculate the restricted mean survival time.
allocationRatioPlanned	Allocation ratio for the active treatment versus control. Defaults to 1 for equal randomization.
accrualTime	A vector that specifies the starting time of piecewise Poisson enrollment time intervals. Must start with 0, e.g., c(0, 3) breaks the time axis into 2 accrual intervals: [0, 3) and [3, Inf).
accrualIntensity	A vector of accrual intensities. One for each accrual time interval.
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.
stratumFraction	A vector of stratum fractions that sum to 1. Defaults to 1 for no stratification.
lambda1	A vector of hazard rates for the event in each analysis time interval by stratum for the active treatment group.
lambda2	A vector of hazard rates for the event in each analysis time interval by stratum for the control group.
gamma1	The hazard rate for exponential dropout, a vector of hazard rates for piecewise exponential dropout applicable for all strata, or a vector of hazard rates for dropout in each analysis time interval by stratum for the active treatment group.
gamma2	The hazard rate for exponential dropout, a vector of hazard rates for piecewise exponential dropout applicable for all strata, or a vector of hazard rates for dropout in each analysis time interval by stratum for the control group.
accrualDuration	Duration of the enrollment period.
followupTime	Follow-up time for the last enrolled subject.
fixedFollowup	Whether a fixed follow-up design is used. Defaults to 0 for variable follow-up.

Value

A data frame containing the following variables:

• time: The calendar time at which to calculate the restricted mean survival time.

• subjects: The number of enrolled subjects.

• milestone: The milestone time relative to randomization.

• rmst1: The restricted mean survival time for the treatment group.

• rmst2: The restricted mean survival time for the control group.

• rmstDiff: The difference in restricted mean survival times, i.e., rmst1 - rmst2.

• vrmst1: The variance for rmst1.

• vrmst2: The variance for rmst2.

• vrmstDiff: The variance for rmstDiff.

• information: The information for rmstDiff, equal to 1/vrmstDiff.

• rmstDiffZ: The Z-statistic value, i.e., rmstDiff/sqrt(vrmstDiff).

Author(s)

Kaifeng Lu, [e-mail]

Examples

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

rmstat(time = c(22, 40),
       milestone = 18,
       allocationRatioPlanned = 1,
       accrualTime = seq(0, 8),
       accrualIntensity = 26/9*seq(1, 9),
       piecewiseSurvivalTime = c(0, 6),
       stratumFraction = c(0.2, 0.8),
       lambda1 = c(0.0533, 0.0309, 1.5*0.0533, 1.5*0.0309),
       lambda2 = c(0.0533, 0.0533, 1.5*0.0533, 1.5*0.0533),
       gamma1 = -log(1-0.05)/12,
       gamma2 = -log(1-0.05)/12,
       accrualDuration = 22,
       followupTime = 18, fixedFollowup = FALSE)

lrstat documentation built on June 23, 2024, 5:06 p.m.