Hi folks, I have a dataset from a trial measuring the subjects' pupils. There are many measurements, all of which must be analysed in a similar fashion; so if I get the analysis right for one of them, I've got them all. For simplicity, let us call any measurement we may be interested as "response". The study design is an unbalanced latin square, with 5 periods, 5 treatments and 6 subjects. Each subject has two measurements: left and right eyes. The model is as follows, with ":" denoting interaction...
Fixed Effects = (Subject + Period + Dose):Eye Random Effects = Subject:Period + Subject:Period:Eye My main question is how to make this happen in R. I know that "aov" is not suitable. If you need any more information, I will do my best to provide it to the best of my knowledge. I'm sort of a new user to statistical software - I've only used R for 3 months so far. So any additional tips would be greatly appreciated. Thanks. :) -- View this message in context: http://r.789695.n4.nabble.com/Unbalanced-Mixed-Linear-Models-With-Nested-Stratum-tp3263969p3263969.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.
