commit 1b3d1829233eea7cbd6172b1df1344c1e0debe03
Author: nwickel <n.wickelmaier@iwm-tuebingen.de>
Date:   Mon Apr 20 16:31:44 2026 +0200

    Initialize repository

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+# Abstract
+
+This workshop will give a short introduction to mixed-effects models for
+longitudinal data. We will look at data sets where data was collected for
+subjects over several time points. The first part will be a basic introduction
+of the concept of random effects and how they extend linear regression. This is
+meant to get everybody on the same page and introduce some notation. We will fit
+the models together in R using the lme4 package. In the second part, we will
+extend the models into growth curve models to model time trends within and
+between subjects. Special focus will be on parameter interpretation and what
+should be kept in mind when fitting and interpreting growth curve models. This
+course is suited for novices to mixed-effects models who want to understand the
+basic concepts, but also for people with a bit more expertise who want to dig
+into more details and deepen their understanding of parameter interpretation.
+
+# Instructor
+
+Dr. Nora Wickelmaier, statistics consultant at the Leibniz-Institut für
+Wissensmedien (IWM), Tübingen
+
+# Prerequisites
+
+Participants will need to have installed:
+
+* a current R version (https://cran.r-project.org/)
+* an IDE for R (like RStudio or VSCode) or a text editor with syntax
+  highlighting (like Vim or Notepad++)
+* the R package lme4 (https://cran.r-project.org/package=lme4)
+