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<!DOCTYPE html>
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<meta charset="utf-8">
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<title>index</title>
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<h2 id="toc-title">On this page</h2>
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<li><a href="#preface" id="toc-preface" class="nav-link active" data-scroll-target="#preface">Preface</a></li>
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<section id="preface" class="level1 unnumbered">
<h1 class="unnumbered">Preface</h1>
<p>In this short introduction we, are going to learn about linear mixed models. We will start with the issues with modelling hierarchical data using simple linear regression. After that, we will formally introduce mixed models and show some applications of them in the context of biological data analysis.</p>
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Note
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<p>This chapter offers an introduction to linear mixed models, focusing on their applications within biological data analysis. It is important to understand that our exploration of mixed models here is not exhaustive. The field of mixed models is extensive and complex, with a variety of techniques and considerations that go beyond the scope of this text. If you seek a comprehensive understanding of the subject, please consult additional resources and literature dedicated to statistical modelling and mixed models. Our goal is to provide a foundational understanding and illustrate the potential of mixed models in addressing hierarchical data challenges in biological research.</p>
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