Torvon
2012-Nov-29 00:07 UTC
[R] Confidence intervals for estimates of all independent variables in WLS regression
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 [[alternative HTML version deleted]]
Jeff Newmiller
2012-Nov-29 00:22 UTC
[R] Confidence intervals for estimates of all independent variables in WLS regression
?summary.lm --------------------------------------------------------------------------- Jeff Newmiller The ..... ..... Go Live... DCN:<jdnewmil at dcn.davis.ca.us> Basics: ##.#. ##.#. Live Go... Live: OO#.. Dead: OO#.. Playing Research Engineer (Solar/Batteries O.O#. #.O#. with /Software/Embedded Controllers) .OO#. .OO#. rocks...1k --------------------------------------------------------------------------- Sent from my phone. Please excuse my brevity. Torvon <torvon at gmail.com> wrote:>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 > > [[alternative HTML version deleted]] > >______________________________________________ >R-help at r-project.org mailing list >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide >http://www.R-project.org/posting-guide.html >and provide commented, minimal, self-contained, reproducible code.
Rui Barradas
2012-Nov-29 13:17 UTC
[R] Confidence intervals for estimates of all independent variables in WLS regression
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 > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.