n1 <- 100
n2 <- 100
set.seed(1234)
par1.1 <- 0
par1.2 <- 1
par2.1 <- 2
par2.2 <- 1
rho <- 0.2
k1 <- rnorm(n1, par1.1, par1.2) # non-diseased
k2 <- rnorm(n2, par2.1, par2.2) # diseased
thres <- thres2(k1, k2, rho, method="eq", ci.method="d")
plot(thres, col=c(1, 2, 4), lwd=c(2, 2, 1), leg.pos="topright")
thresunequal <- thres2(k1, k2, rho, method="unequal", ci=FALSE)
lines(thresunequal, col=3) # almost the same; no confidence interval
if (FALSE) {
thresboot <- thres2(k1, k2, rho, method="emp", ci.method="b")
lines(thresboot, col=5, which.boot="norm")
}
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