wlrcal: A utility function to calculate the weighted log-rank...

In PWEALL: Design and Monitoring of Survival Trials Accounting for Complex Situations

A utility function to calculate the weighted log-rank statistics and their varainces given the weights

Description

A utility function to calculate the weighted log-rank statistics and their varainces given the weights

Usage

wlrcal(n=10,te=c(1,2,3),tfix=2.0,dd1=c(1,0,1),dd0=c(0,1,0),r1=c(1,2,3),r0=c(1,2,3),
       weights=matrix(1,nrow=length(te),ncol=1),eps=1.0e-08)

Arguments

n	total number of subjects in the study
te	(ascendingly) ordered unique event times from both groups
tfix	time point where weighted log-rank is calcualted
dd1	number of events from treatment group at each te
dd0	number of events from control group at each te
r1	number of at-risk subjects from treatment group at each te
r0	number of at-risk subjects from control group at each te
weights	user specified weights, each column is a set of weights at each te
eps	tolerence when comparing event times

Details

More details

Value

test	unscaled test statistics
var	variances of the unsclaed test statistics
wlr	weighted log-rank statistics, i.e. scaled test statsitics
wlcor	the correlation matrix of the weighted log-rank statistics

Author(s)

Xiaodong Luo

Examples

lr<-wlrcal(n=10,te=c(1,2,3),tfix=2.0,dd1=c(1,0,1),dd0=c(0,1,0),r1=c(1,2,3),r0=c(1,2,3))
lr

PWEALL documentation built on Aug. 9, 2023, 9:08 a.m.