lrstat (version 0.2.13)

kmstat1: Milestone Survival Probability by Stratum

Description

Obtains the milestone survival probability and associated variance by treatment group and by stratum at a given calendar time.

Usage

kmstat1(
  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
)

Value

A data frame containing the following variables:

• stratum: The stratum.

• time: The calendar time since trial start.

• subjects: The number of enrolled subjects.

• nevents: The total number of events.

• nevents1: The number of events in the active treatment group.

• nevents2: The number of events in the control group.

• ndropouts: The total number of dropouts.

• ndropouts1: The number of dropouts in the active treatment group.

• ndropouts2: The number of dropouts in the control group.

• milestone: The milestone time relative to randomization.

• nmilestone: The total number of subjects reaching milestone.

• nmilestone1: The number of subjects reaching milestone in the active treatment group.

• nmiletone2: The number of subjects reaching milestone in the control group.

• surv1: The milestone survival probability for the treatment group.

• surv2: The milestone survival probability for the control group.

• survDiff: The difference in milestone survival probabilities, i.e., surv1 - surv2.

• vsurv1: The variance for surv1.

• vsurv2: The variance for surv2.

• vsurvDiff: The variance for survDiff.

Arguments

time

The calendar time for data cut.

milestone

The milestone time at which to calculate the survival probability.

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.

Author

Kaifeng Lu,

Examples

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

kmstat1(time = 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)