lrpowerequiv: Power for equivalence in hazard ratio

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

Power for equivalence in hazard ratio

Description

Obtains the power for equivalence in hazard ratio.

Usage

lrpowerequiv(
  kMax = 1L,
  informationRates = NA_real_,
  criticalValues = NA_real_,
  alpha = 0.05,
  typeAlphaSpending = "sfOF",
  parameterAlphaSpending = NA_real_,
  userAlphaSpending = NA_real_,
  hazardRatioLower = NA_real_,
  hazardRatioUpper = 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,
  typeOfComputation = "direct",
  spendingTime = NA_real_,
  studyDuration = NA_real_
)

Arguments

kMax	The maximum number of stages.
informationRates	The information rates. Defaults to (1:kMax) / kMax if left unspecified.
criticalValues	Upper boundaries on the z-test statistic scale for stopping for efficacy.
alpha	The significance level for each of the two one-sided tests. Defaults to 0.05.
typeAlphaSpending	The type of alpha spending. One of the following: "OF" for O'Brien-Fleming boundaries, "P" for Pocock boundaries, "WT" for Wang & Tsiatis boundaries, "sfOF" for O'Brien-Fleming type spending function, "sfP" for Pocock type spending function, "sfKD" for Kim & DeMets spending function, "sfHSD" for Hwang, Shi & DeCani spending function, "user" for user defined spending, and "none" for no early efficacy stopping. Defaults to "sfOF".
parameterAlphaSpending	The parameter value for the alpha spending. Corresponds to Delta for "WT", rho for "sfKD", and gamma for "sfHSD".
userAlphaSpending	The user defined alpha spending. Cumulative alpha spent up to each stage.
hazardRatioLower	The lower equivalence limit of hazard ratio.
hazardRatioUpper	The upper equivalence limit of hazard ratio.
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.
typeOfComputation	The type of computation, either "direct" for the direct approximation method, or "schoenfeld" for the Schoenfeld method. Defaults to "direct". Can use "Schoenfeld" under proportional hazards and conventional log-rank test.
spendingTime	A vector of length kMax for the error spending time at each analysis. Defaults to missing, in which case, it is the same as informationRates.
studyDuration	Study duration for fixed follow-up design. Defaults to missing, which is to be replaced with the sum of accrualDuration and followupTime. If provided, the value is allowed to be less than the sum of accrualDuration and followupTime.

Value

An S3 class lrpowerequiv object with 4 components:

• overallResults: A data frame containing the following variables:

  • overallReject: The overall rejection probability.

  • alpha: The overall significance level.

  • attainedAlphaH10: The attained significance level under H10.

  • attainedAlphaH20: The attained significance level under H20.

  • numberOfEvents: The total number of events.

  • numberOfDropouts: The total number of dropouts.

  • numbeOfSubjects: The total number of subjects.

  • studyDuration: The total study duration.

  • information: The maximum information.

  • expectedNumberOfEvents: The expected number of events.

  • expectedNumberOfDropouts: The expected number of dropouts.

  • expectedNumberOfSubjects: The expected number of subjects.

  • expectedStudyDuration: The expected study duration.

  • expectedInformation: The expected information.

  • kMax: The number of stages.

  • hazardRatioLower: The lower equivalence limit of hazard ratio.

  • hazardRatioUpper: The upper equivalence limit of hazard ratio.

  • accrualDuration: The accrual duration.

  • followupTime: The follow-up time.

  • fixedFollowup: Whether a fixed follow-up design is used.

• byStageResults: A data frame containing the following variables:

  • informationRates: The information rates.

  • efficacyBounds: The efficacy boundaries on the Z-scale for each of the two one-sided tests.

  • rejectPerStage: The probability for efficacy stopping.

  • cumulativeRejection: The cumulative probability for efficacy stopping.

  • cumulativeAlphaSpent: The cumulative alpha for each of the two one-sided tests.

  • cumulativeAttainedAlphaH10: The cumulative alpha attained under H10.

  • cumulativeAttainedAlphaH20: The cumulative alpha attained under H20.

  • numberOfEvents: The number of events.

  • numberOfDropouts: The number of dropouts.

  • numberOfSubjects: The number of subjects.

  • analysisTime: The average time since trial start.

  • efficacyHRLower: The efficacy boundaries on the hazard ratio scale for the one-sided null hypothesis at the lower equivalence limit.

  • efficacyHRUpper: The efficacy boundaries on the hazard ratio scale for the one-sided null hypothesis at the upper equivalence limit.

  • efficacyP: The efficacy bounds on the p-value scale for each of the two one-sided tests.

  • information: The cumulative information.

  • HR: The average hazard ratio.

• settings: A list containing the following input parameters: typeAlphaSpending, parameterAlphaSpending, userAlphaSpending, allocationRatioPlanned, accrualTime, accuralIntensity, piecewiseSurvivalTime, stratumFraction, lambda1, lambda2, gamma1, gamma2, typeOfComputation, and spendingTime.

• byTreatmentCounts: A list containing the following counts by treatment group:

  • numberOfEvents1: The number of events by stage for the treatment group.

  • numberOfDropouts1: The number of dropouts by stage for the treatment group.

  • numberOfSubjects1: The number of subjects by stage for the treatment group.

  • numberOfEvents2: The number of events by stage for the control group.

  • numberOfDropouts2: The number of dropouts by stage for the control group.

  • numberOfSubjects2: The number of subjects by stage for the control group.

  • expectedNumberOfEvents1: The expected number of events for the treatment group.

  • expectedNumberOfDropouts1: The expected number of dropouts for the treatment group.

  • expectedNumberOfSubjects1: The expected number of subjects for the treatment group.

  • expectedNumberOfEvents2: The expected number of events for control group.

  • expectedNumberOfDropouts2: The expected number of dropouts for the control group.

  • expectedNumberOfSubjects2: The expected number of subjects for the control group.

Author(s)

Kaifeng Lu, [e-mail]

See Also

rmstat

Examples

lrpowerequiv(kMax = 2, informationRates = c(0.5, 1),
             alpha = 0.05, typeAlphaSpending = "sfOF",
             hazardRatioLower = 0.71, hazardRatioUpper = 1.4,
             allocationRatioPlanned = 1, accrualTime = seq(0, 8),
             accrualIntensity = 100/9*seq(1, 9),
             piecewiseSurvivalTime = c(0, 6),
             stratumFraction = c(0.2, 0.8),
             lambda1 = c(0.0533, 0.0533, 1.5*0.0533, 1.5*0.0533),
             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.