hi all - i'm having trouble using lme to specify a mixed effects model. i'm pretty sure this is quite easy for the experienced anova-er, which i unfortunately am not.
i have a data frame with the following columns: col 1 : "Score1" (this is a continuous numeric measure between 0 and 1) col 2 : "Score2" (another continuous numeric measure, this time bounded between 0 and 100) col 3 : "Class" (a fixed-effects factor with 4 (ordered) levels) i have ~2000 observations, but unbalanced w.r.t. the "Class" factor. each observation has a distinct "Score1" and "Score2". i'd like to try a mixed-effect anova model where "Score1" is the dependent response, and "Score2" and "Class" are the explanatory covariates (with an expected interaction between them). naively, i simply tried: aov(Score1 ~ Score2 * Class) but i'm pretty sure this treated "Score2" as a fixed-effects covariate with a single observation per level. can anyone help guide me to the correct model specification using lme(...)? thanks much for any help! ______________________________________________ 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.
