Computes the standardized score processes
score.proc.Rd
Computes the standarized score processes for the covariates.
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
Examples
library(WR)
head(non_ischemic)
#> ID time status trt_ab age sex Black.vs.White Other.vs.White bmi bipllvef
#> 1 1 221 2 0 62 1 0 0 25.18 32.24
#> 2 1 383 0 0 62 1 0 0 25.18 32.24
#> 3 2 23 2 0 75 1 1 0 22.96 21.71
#> 4 2 1400 0 0 75 1 1 0 22.96 21.71
#> 5 5 7 2 0 48 1 1 0 34.37 22.97
#> 6 5 10 1 0 48 1 1 0 34.37 22.97
#> hyperten COPD diabetes acei betab smokecurr
#> 1 0 0 0 0 1 1
#> 2 0 0 0 0 1 1
#> 3 1 0 0 0 1 0
#> 4 1 0 0 0 1 0
#> 5 1 0 0 0 1 0
#> 6 1 0 0 0 1 0
# 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)