Interim Monitoring Using Adaptively Weighted Log-Rank Test in Clinical Trials

For any spending function specified by the user, this package provides corresponding boundaries for interim testing using the adaptively weighted log-rank test developed by Yang and Prentice (2010 ). The package uses a re-sampling method to obtain stopping boundaries at the interim looks.The output consists of stopping boundaries and observed values of the test statistics at the interim looks, along with nominal p-values defined as the probability of the test exceeding the specific observed test statistic value or critical value, regardless of the test behavior at other looks. The asymptotic validity of the stopping boundaries is established in Yang (2018 ).



output: html_document: default pdf_document: default

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).

Installation

install.packages("YPInterimTesting")

Example

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)

Reference

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.

News

YPInterimTesting 1.0.2

  • Fix error in setting random seed in the 'ypinterm.default' function

YPInterimTesting 1.0.1

  • Fix error when setting a random.seed

YPInterimTesting 1.0.0

  • Add error messages to ypinterim.default to help users detect common errors easily.

  • Fixing errors when critvalue is supplied in the ypinterim function.

  • the argument name of spenfun in the ypinterim function is changed to spendfun.

  • When the alpha spent is less than 1E-4, the boundaries of that look and the corresponding nominal p-values are now obtained using a (conditional) normal distribution.

  • When the value of the observed statistic is greater than qnorm(1 - 1E-4/2), the nominal p-values are now obtained using a normal distribution.

  • The default value for repnum is set to 1E4.

  • The the results from print and summary of the ypinterim class now show the nominal p-values for the boundaries.

  • Update the references on the help documents and the DESCRIPTION file as they are now available online.

  • Add new examples to the ypinterim help documents in order to show how to utilize the argument critvalue in the function clearly.

  • Error fixed in the example data: the virtual_data has also been changed to have only one group vector.

YPInterimTesting 0.1.0

  • The initial version

Reference manual

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install.packages("YPInterimTesting")

1.0.3 by Daewoo Pak, 5 months ago


Browse source code at https://github.com/cran/YPInterimTesting


Authors: Daewoo Pak and Song Yang


Documentation:   PDF Manual  


GPL (>= 3) license


Imports Rcpp, MASS

Linking to Rcpp


See at CRAN