The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
The goal of lrstat is to calculate power and sample size under non-proportional hazards using weighted log-rank tests both analytically and using simulations in a time-to-event group-sequential trial.
It has built-in capabilities to use error-spending functions and can calcualte power, accrual duration, follow-up duration, and absolute accrual rates for the Fleming-Harrington’s class of weighting functions.
This is a basic example which shows you how to solve a common problem:
library(lrstat)
## basic example code for a two-stage group sequential trial with interim
## analysis at 80% of total number of events using Lan-DeMets O'Brien-Fleming
## error-spending. The accrual has a ramp-up periof of 9 months before
## reaching 26 patients per month. The survival distribution for the treatment
## group has a delay effect of 6 months and a hazard ratio 0.58 after the delay.
## The annual dropout rate is 5%. The accrual duration is 22 months.
## The follow-up duration is 18 months for the last randomized patients.
## The FH(0,1) weighted log-rank test is used for power calculation.
lrpower(kMax = 2, informationRates = c(0.8, 1),
alpha = 0.025, typeAlphaSpending = "sfOF",
allocationRatioPlanned = 1, accrualTime = seq(0, 9),
accrualIntensity = c(26/9*seq(1, 9), 26),
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,
rho1 = 0, rho2 = 1,
numSubintervals = 2000)These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.