Obtains the sample size and study duration by calibrating the number of events calculated using the Schoenfeld formula under the proportional hazards assumption.
lrschoenfeld(
beta = 0.2,
kMax = 1L,
informationRates = NA_real_,
efficacyStopping = NA_integer_,
futilityStopping = NA_integer_,
criticalValues = NA_real_,
alpha = 0.025,
typeAlphaSpending = "sfOF",
parameterAlphaSpending = NA_real_,
userAlphaSpending = NA_real_,
futilityBounds = NA_real_,
typeBetaSpending = "none",
parameterBetaSpending = NA_real_,
userBetaSpending = NA_real_,
hazardRatioH0 = 1,
allocationRatioPlanned = 1,
accrualTime = 0L,
accrualIntensity = NA_real_,
piecewiseSurvivalTime = 0L,
stratumFraction = 1L,
hazardRatio = NA_real_,
lambda2 = NA_real_,
gamma1 = 0L,
gamma2 = 0L,
followupTime = NA_real_,
fixedFollowup = 0L,
interval = as.numeric(c(0.001, 240)),
spendingTime = NA_real_,
rounding = 1L,
calibrate = 1L,
maxNumberOfIterations = 10000L,
maxNumberOfRawDatasetsPerStage = 0L,
seed = NA_integer_
)A list of two components:
resultsUnderH1: An S3 class lrpower object under the
alternative hypothesis.
resultsUnderH0: An S3 class lrpower object under the
null hypothesis.
Type II error. Defaults to 0.2.
The maximum number of stages.
The information rates in terms of number
of events for the conventional log-rank test and in terms of
the actual information for weighted log-rank tests.
Defaults to (1:kMax) / kMax if left unspecified.
Indicators of whether efficacy stopping is allowed at each stage. Defaults to true if left unspecified.
Indicators of whether futility stopping is allowed at each stage. Defaults to true if left unspecified.
Upper boundaries on the z-test statistic scale for stopping for efficacy.
The significance level. Defaults to 0.025.
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".
The parameter value for the alpha spending. Corresponds to Delta for "WT", rho for "sfKD", and gamma for "sfHSD".
The user defined alpha spending. Cumulative alpha spent up to each stage.
Lower boundaries on the z-test statistic scale
for stopping for futility at stages 1, ..., kMax-1. Defaults to
rep(-6, kMax-1) if left unspecified. The futility bounds are
non-binding for the calculation of critical values.
The type of beta spending. One of the following: "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 futility stopping. Defaults to "none".
The parameter value for the beta spending. Corresponds to rho for "sfKD", and gamma for "sfHSD".
The user defined beta spending. Cumulative beta spent up to each stage.
Hazard ratio under the null hypothesis for the active treatment versus control. Defaults to 1 for superiority test.
Allocation ratio for the active treatment versus control. Defaults to 1 for equal randomization.
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).
A vector of accrual intensities. One for each accrual time interval.
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.
A vector of stratum fractions that sum to 1. Defaults to 1 for no stratification.
Hazard ratio under the alternative hypothesis for the active treatment versus control.
A vector of hazard rates for the event in each analysis time interval by stratum for the control group.
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.
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.
Follow-up time for the last enrolled subject.
Whether a fixed follow-up design is used. Defaults to 0 for variable follow-up.
The interval to search for the solution of
followupTime. Defaults to c(0.001, 240).
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.
Whether to round up sample size and events. Defaults to 1 for sample size rounding.
Whether to use simulations to calibrate the number of events calculated using the Schoenfeld formula.
The number of simulation iterations. Defaults to 10000.
The number of raw datasets per stage to extract.
The seed to reproduce the simulation results. The seed from the environment will be used if left unspecified.
Kaifeng Lu, kaifenglu@gmail.com
(lr1 <- lrschoenfeld(
beta = 0.1, kMax = 2, alpha = 0.025,
hazardRatioH0 = 1, allocationRatioPlanned = 1,
accrualIntensity = 20, hazardRatio = 0.3,
lambda2 = 1.9/12,
gamma1 = -log(1-0.1)/24, gamma2 = -log(1-0.1)/24,
fixedFollowup = 0, rounding = 1,
calibrate = 0, maxNumberOfIterations = 1000,
seed = 12345))
(lr2 <- lrschoenfeld(
beta = 0.1, kMax = 2, alpha = 0.025,
hazardRatioH0 = 1, allocationRatioPlanned = 1,
accrualIntensity = 20, hazardRatio = 0.3,
lambda2 = 1.9/12,
gamma1 = -log(1-0.1)/24, gamma2 = -log(1-0.1)/24,
fixedFollowup = 0, rounding = 1,
calibrate = 1, maxNumberOfIterations = 1000,
seed = 12345))
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