Hi everyone, I'm fairly new to R, and I don't have a background in statistics, so please bear with me. ;-)
I'm dealing with 2^k factorial designs, and I was just wondering if there's any way to analyze more than two factors of a gage R&R study in R. For example, Minitab has an "expanded gage R&R" function that lets you include up to eight additional factors besides the usual two that are present in gage studies (parts and operators). If I wanted to include n additional random factors, is there a package or built-in functionality that will allow me to do that? I've been experimenting with the SixSigma package, and that has a ss.rr method which works great---as long as your experiment only contains two factors. I've also been using lmer from lme4 to fit a linear model of my experiment, but the standard deviations generated by lmer don't match what I'm seeing in Minitab. Since all my factors are random, the formula I'm using looks like this: vals ~ 1 + (1|f1) + (1|f2) + (1|f3) + (1|f1:f2) + (1|f1:f3) + (1|f2:f3) What am I doing wrong, and how can I fix it? Thanks, Matt ______________________________________________ R-help@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.
