Hi Georg, Instead of stratifying by sex, use all your data together to fit one model that controls for sex. This gives you more power because of the increased sample size. Also, this way you can add an interaction term, which is what you are looking for. The gender variable should be defined as a factor. Here's an example:
dataframe$sex <- factor(dataframe$sex) awesomemodel <- lm(outcomevariable ~ sex + x + sex*x, data = dataframe) Hope this helps, JoAnn ________________________________________ From: [email protected] [[email protected]] On Behalf Of Georg Ehret [[email protected]] Sent: Sunday, April 04, 2010 5:01 PM To: r-help Subject: [R] calculating an interaction statistic from stratified data Dear R community, I have data on beta&standard error (for the main effect of variable x), stratified by sex for my dataset. I wish to calculate the sex-interaction effect (as beta&se) from these two stratified datasets. Is there a package to do this? If not, any advice how to do it manually? Thank you very much and best regards, Georg. ************************ Georg Ehret, JHU, Baltimore [[alternative HTML version deleted]] ______________________________________________ [email protected] 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. ______________________________________________ [email protected] 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.
