lrstat1 | R Documentation |
Obtains the number of subjects having an event in each treatment group by stratum, the mean and variance of weighted log-rank score statistic for a hypothesized hazard ratio at a given calendar time.
lrstat1(
time = NA_real_,
hazardRatioH0 = 1,
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,
rho1 = 0,
rho2 = 0,
numSubintervals = 300L,
predictEventOnly = 0L
)
time |
The calendar time at which to calculate the number of events and the mean and variance of log-rank test score statistic. |
hazardRatioH0 |
Hazard ratio under the null hypothesis for the active treatment versus control. Defaults to 1 for superiority test. |
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.,
|
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. |
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. |
rho1 |
The first parameter of the Fleming-Harrington family of weighted log-rank test. Defaults to 0 for conventional log-rank test. |
rho2 |
The second parameter of the Fleming-Harrington family of weighted log-rank test. Defaults to 0 for conventional log-rank test. |
numSubintervals |
Number of sub-intervals to approximate the mean and variance of the weighted log-rank test score statistic. Defaults to 300. Specify a larger number for better approximation. |
predictEventOnly |
Whether to predict the number of events only. Defaults to 0 for obtaining log-rank test score statistic mean and variance. |
A data frame of the following variables if
predictEventOnly = 1
:
stratum
: The stratum number.
time
: The analysis 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.
nfmax
: The total number of subjects reaching maximum follow-up.
nfmax1
: The number of subjects reaching maximum follow-up in
the active treatment group.
nfmax2
: The number of subjects reaching maximum follow-up in
the control group.
If predictEventOnly = 0
, the following variables will also
be included:
uscore
: The numerator of the weighted log-rank test statistic.
vscore
: The variance of the weighted log-rank score statistic
with weight squared.
iscore
: The Fisher information of the weighted log-rank score
statistic.
Kaifeng Lu, kaifenglu@gmail.com
# Piecewise accrual, piecewise exponential survivals, and 5% dropout by
# the end of 1 year.
lrstat1(time = 22, hazardRatioH0 = 1,
allocationRatioPlanned = 1,
accrualTime = seq(0, 8),
accrualIntensity = 26/9*seq(1, 9),
piecewiseSurvivalTime = c(0, 6),
lambda1 = c(0.0533, 0.0309),
lambda2 = c(0.0533, 0.0533),
gamma1 = -log(1-0.05)/12,
gamma2 = -log(1-0.05)/12,
accrualDuration = 22,
followupTime = 18, fixedFollowup = FALSE)
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