score.proc: Computes the standardized score processes

In WR: Win Ratio Analysis of Composite Time-to-Event Outcomes

Description

Computes the standarized score processes for the covariates.

Usage

score.proc(obj, t = NULL)

Arguments

obj	an object of class pwreg.
t	a vector containing times. If not specified, the function will use all unique event times from the data.

Value

An object of class pwreg.score consisting of t: a vector of times; and score: a matrix whose rows are the standardized score processes as a function of t.

References

Mao, L. and Wang, T. (2020). A class of proportional win-fractions regression models for composite outcomes. Biometrics, 10.1111/biom.13382

See Also

pwreg, print.pwreg

Examples

library(WR)
head(non_ischemic)

# Randomly sample 200 subjects from non_ischemic data
id_unique <-unique(non_ischemic$ID)
set.seed(2019)
id_sample <- sample(id_unique, 200)
non_ischemic_reduce <- non_ischemic[non_ischemic$ID %in% id_sample, ]

# Use the reduced non_ischemic data for analysis
nr <- nrow(non_ischemic_reduce)
p <- ncol(non_ischemic_reduce)-3
ID <- non_ischemic_reduce[,"ID"]
time <- non_ischemic_reduce[,"time"]
status <- non_ischemic_reduce[,"status"]
Z <- as.matrix(non_ischemic_reduce[,4:(3+p)],nr,p)
pwreg.obj <- pwreg(time=time,status=status,Z=Z,ID=ID)
score.obj <- score.proc(pwreg.obj)
#plot the standardized score process for the first covariate
plot(score.obj, k = 1)

WR documentation built on Nov. 27, 2021, 1:06 a.m.