I have a data frame with two variables that are factors. One is actually a TRUE/FALSE factor, and I have coded it as 1/0, a continuous variable, but I could turn it back into a factor. The second is an ordered factor and consists of five timepoints. There are several continuous variables as well. Now I want to fit a linear model to my data, using lm (or another R procedure if recommended).
Question: should I use polynomial contrasts? My timepoints are very far from being evenly spaced, so ordinary R contrasts seem more natural. But I'm totally inexperienced (this is my first serious regression). I also want to choose my base value. In the first call to lm, I want to choose base value equal to FirstTimePoint. In my second call to lm, I want to choose base value to be the interaction term FirstTimePoint:FALSE or FirstTimePoint:0. Does all this make sense? Please excuse my inexperience if it doesn't. If it makes sense, then there must be two simple calls to lm. But I'm floundering. Thanks a lot David -- View this message in context: http://n4.nabble.com/simple-question-about-contrasts-lm-and-factors-tp1835964p1835964.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.