Hello,
Try the following function.
ci_lm <- function(object, level = 0.95){
summfit <- summary(object)
beta <- summfit$coefficients[, 1]
se <- summfit$coefficients[, 2]
df <- summfit$df[1]
alpha <- 1 - level
lower <- beta + qt(alpha/2, df = df)*se
upper <- beta + qt(1 - alpha/2, df = df)*se
data.frame(beta, lower, upper)
}
Hope this helps,
Rui Barradas
Em 29-11-2012 00:07, Torvon escreveu:
I would like to obtain Confidence Intervals for the estimates
(unstandardized beta weights) of each predictor in a WLS regression:
m1 = lm(x~ x1+x2+x3, weights=W, data=D)
SPSS offers that output by default, and I am not able to find a way to do
this in R. I read through predict.lm, but I do not find a way to get the
CIs for multiple independent variables.
Thank you
Torvon
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