inst/tests/lrmMean.s

In rms: Regression Modeling Strategies

require(rms)
set.seed(6) # was 3
n <- 100
y <- sample(1:10, n, TRUE)
# Do minimal combining of levels to ensure bootstraps will sample all values
y <- round(ordGroupBoot(y), 3)
x1 <- runif(n)
f <- lrm(y ~ x1, x=TRUE, y=TRUE)
g <- bootcov(f, B=500, coef.reps=TRUE)
m <- Mean(f)

Predict(f, x1=c(.25, .75), fun=m) #
Predict(g, x1=c(.25, .75), fun='mean')
h <- ols(y ~ x1)
Predict(h, x1=c(.25, .75))