rmpower1s | R Documentation |
Estimates the power, stopping probabilities, and expected sample size in a one-group survival design.
rmpower1s(
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_,
milestone = NA_real_,
rmstH0 = NA_real_,
accrualTime = 0L,
accrualIntensity = NA_real_,
piecewiseSurvivalTime = 0L,
stratumFraction = 1L,
lambda = NA_real_,
gamma = 0L,
accrualDuration = NA_real_,
followupTime = NA_real_,
fixedFollowup = 0L,
spendingTime = NA_real_,
studyDuration = NA_real_
)
kMax |
The maximum number of stages. |
informationRates |
The information rates.
Defaults to |
efficacyStopping |
Indicators of whether efficacy stopping is allowed at each stage. Defaults to true if left unspecified. |
futilityStopping |
Indicators of whether futility stopping is allowed at each stage. Defaults to true if left unspecified. |
criticalValues |
Upper boundaries on the z-test statistic scale for stopping for efficacy. |
alpha |
The significance level. Defaults to 0.025. |
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. |
futilityBounds |
Lower boundaries on the z-test statistic scale
for stopping for futility at stages 1, ..., |
typeBetaSpending |
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, and "none" for no early futility stopping. Defaults to "none". |
parameterBetaSpending |
The parameter value for the beta spending. Corresponds to rho for "sfKD", and gamma for "sfHSD". |
milestone |
The milestone time at which to calculate the restricted mean survival time. |
rmstH0 |
The restricted mean survival time under the null hypothesis. |
accrualTime |
A vector that specifies the starting time of
piecewise Poisson enrollment time intervals. Must start with 0, e.g.,
|
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.,
|
stratumFraction |
A vector of stratum fractions that sum to 1. Defaults to 1 for no stratification. |
lambda |
A vector of hazard rates for the event in each analysis time interval by stratum under the alternative hypothesis. |
gamma |
The hazard rate for exponential dropout or a vector of hazard rates for piecewise exponential dropout. Defaults to 0 for no dropout. |
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. |
spendingTime |
A vector of length |
studyDuration |
Study duration for fixed follow-up design.
Defaults to missing, which is to be replaced with the sum of
|
An S3 class rmpower1s
object with 3 components:
overallResults
: A data frame containing the following variables:
overallReject
: The overall rejection probability.
alpha
: The overall significance level.
drift
: The drift parameter, equal to
(rmst - rmstH0)*sqrt(information)
.
inflationFactor
: The inflation factor (relative to the
fixed design).
numbeOfSubjects
: The total number of subjects.
studyDuration
: The total study duration.
information
: The maximum information.
expectedNumberOfSubjects
: The expected number of subjects.
expectedStudyDuration
: The expected study duration.
expectedInformation
: The expected information.
accrualDuration
: The accrual duration.
followupTime
: The follow-up duration.
fixedFollowup
: Whether a fixed follow-up design is used.
kMax
: The number of stages.
milestone
: The milestone time relative to randomization.
rmstH0
: The restricted mean survival time under the null
hypothesis.
rmst
: The restricted mean survival time under the
alternative hypothesis.
byStageResults
: A data frame containing the following variables:
informationRates
: The information rates.
efficacyBounds
: The efficacy boundaries on the Z-scale.
futilityBounds
: The futility boundaries on the Z-scale.
rejectPerStage
: The probability for efficacy stopping.
futilityPerStage
: The probability for futility stopping.
cumulativeRejection
: The cumulative probability for efficacy
stopping.
cumulativeFutility
: The cumulative probability for futility
stopping.
cumulativeAlphaSpent
: The cumulative alpha spent.
numberOfSubjects
: The number of subjects.
analysisTime
: The average time since trial start.
efficacyRmst
: The efficacy boundaries on the restricted
mean survival time.
futilityRmst
: The futility boundaries on the restricted
mean survival time.
efficacyP
: The efficacy boundaries on the p-value scale.
futilityP
: The futility boundaries on the p-value scale.
information
: The cumulative information.
efficacyStopping
: Whether to allow efficacy stopping.
futilityStopping
: Whether to allow futility stopping.
settings
: A list containing the following input parameters:
typeAlphaSpending
, parameterAlphaSpending
,
userAlphaSpending
, typeBetaSpending
,
parameterBetaSpending
, accrualTime
,
accuralIntensity
, piecewiseSurvivalTime
,
stratumFraction
, lambda
, gamma
,
and spendingTime
.
Kaifeng Lu, kaifenglu@gmail.com
rmstat
rmpower1s(kMax = 2, informationRates = c(0.8, 1),
alpha = 0.025, typeAlphaSpending = "sfOF",
milestone = 18, rmstH0 = 10,
accrualTime = seq(0, 8),
accrualIntensity = 26/9*seq(1, 9),
piecewiseSurvivalTime = c(0, 6),
stratumFraction = c(0.2, 0.8),
lambda = c(0.0533, 0.0309, 1.5*0.0533, 1.5*0.0309),
gamma = -log(1-0.05)/12, accrualDuration = 22,
followupTime = 18, fixedFollowup = FALSE)
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