Monday, November 21, 2011. 14h-16hCristian CorreaLinear mixed-effects models describe the relationship between a continuous response variable and some covariates where at least one of the covariates in the model is a categorical variable. This categorical variable may represent the subject or study location, or more generally, the observational unit. If the discrete levels of this categorical variable are chosen at random this represents a random effects.Objectives- Learn the difference between
*fixed*and*random*effects and when data should be modelled with a combination of these effects, namely,*mixed-effects models.* - Use an example dataset to learn the R code needed to run a LMM (i.e, Linear Mixed-effects).
PrerequisitesPlease install the lme4, ggplot2, arm, and MASS packages for R before the start of the workshop. If you are having trouble with this, please come at least 15 minutes early and we will be happy to assist you. SlidesDownload slides here. |