31 lines
1.3 KiB
Markdown
31 lines
1.3 KiB
Markdown
# Abstract
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This workshop will give a short introduction to linear mixed-effects models with
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an example from educational science. We will look at a hierarchical data set
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containing students in schools. The first part will be a basic introduction of
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the concept of random effects and how they extend linear regression. This is
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meant to get everybody on the same page and introduce some notation. We will fit
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these simple models together in R using the lme4 package. In the second part, a
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more complex hierarchical model will be introduced. We will try to understand
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how models like these can be used to answer research questions concerning
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different levels of the data. Again, we will use R to fit this model. This
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course is suited for novices to mixed-effects models who want to understand the
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basic concepts, but also for people with a bit more expertise using hierarchical
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models who want to dig into more details and deepen their understanding of
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parameter interpretation.
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# Instructor
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Dr. Nora Wickelmaier, statistics consultant at the Leibniz-Institut für
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Wissensmedien (IWM), Tübingen
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# Prerequisites
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Participants will need to have installed:
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* a current R version (https://cran.r-project.org/)
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* an IDE for R (like RStudio or VSCode) or a text editor with syntax
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highlighting (like Vim or Notepad++)
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* the R package lme4 (https://cran.r-project.org/package=lme4)
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