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.
Provide monitoring boundaries and nominal p-values at the interim looks using the adaptively weighted log-rank test developed by Yang and Prentice (2010). The package use a re-sampling method to obtain stopping boundaries in sequential designs. The asymptotic distribution of the test statistics of the adaptively weighted log-rank test at the interim looks is examined in Yang (2018).
install.packages("YPInterimTesting")library(YPInterimTesting)
data(virtual_data) # the data created to show how to utilize the package
time <- virtual$time
event <- virtual$event
group <- virtual$group
spendfun <- c(1.3E-5, 4.4E-4, 0.003, 0.008)
result_all <- ypinterim(time, event, group, spendfun=spendfun)
result_all
summary(result_all)
The above example shows how to test the package with a historical
data where interim data at all looks are available. The object
result_all can be formatted to a table using the function
summary.
summary(result)The known boundaries of the first few looks can be supplied using
crtivalue. The following three examples show how to supply
crtivalue when the boundaries at the previous looks
exist.
We first need to calculate the boundary at the first look. The spending function value at the first look is needed.
# Assume that we only have the information on the first look
time <- virtual$time[, 1]
event <- virtual$event[, 1]
group <- virtual$group
spendfun <- c(1.3E-5)
result_look1 <- ypinterim(time, event, group, spendfun=spendfun)
result_look1
summary(result_look1)When calculating the boundary at the second look, the spending function at the two looks, and boundary at the first look (i.e., the value obtained from the previous example), should be supplied.
time <- virtual$time[, 1:2]
event <- virtual$event[, 1:2]
group <- virtual$group
spendfun <- c(1.3E-5, 4.4E-4)
critvalue <- c(4.36) # the boundary of the first look is supplied.
result_look2 <- ypinterim(time, event, group, spendfun=spendfun, critvalue = critvalue)
result_look2
summary(result_look2)Similarly, when calculating the boundary at the third look, the spending function at the three looks, and boundaries at the first two looks, should be supplied.
time <- virtual$time[, 1:3]
event <- virtual$event[, 1:3]
group <- virtual$group
spendfun <- c(1.3E-5, 4.4E-4, 0.003)
critvalue <- c(4.36, 3.42) # the boundaries at the first two looks are supplied.
result_look3 <- ypinterim(time, event, group, spendfun=spendfun, critvalue = critvalue)
result_look3
summary(result_look3)Yang, S. (2018). Interim monitoring using the adaptively weighted log-rank test in clinical trials for survival outcomes. Statistics in Medicine.
Yang, S., & Prentice, R. (2010). Improved logrank-type tests for survival data using adaptive weights. Biometrics, 66(1), 30-38.
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.