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Module M.5 Linear mixed-effects models

Author(s): Raisa Hernández-Pacheco1, Alexandra L Bland1, Alexis A Diaz1, Alexandra G Rosati2

1. California State University, Long Beach 2. University of Michigan

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Summary:
Introduction to Primate Data Exploration and Linear Modeling with R was created with the goal of providing training to undergraduate biology students on data management and statistical analysis using authentic data of Cayo Santiago rhesus macaques.…

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Introduction to Primate Data Exploration and Linear Modeling with R was created with the goal of providing training to undergraduate biology students on data management and statistical analysis using authentic data of Cayo Santiago rhesus macaques. Module M.5 introduces linear mixed-effects modeling in R.

Licensed under Creative Commons CC0 1.0 Universal

Version 1.0 - published on 26 Jun 2023 doi:10.25334/J6C1-MQ50 - cite this

Keywords

  1. R programming language
  2. primates
  3. population ecology

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  5. Open Science and Education Practices Ontology
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Description

In Module M.5, we introduce basic functions in R, as well as in its package lmerTest, to fit linear mixed-effects models to authentic data from Cayo Santiago rhesus macaques. Module M.5 is part of the 8-module series Introduction to Primate Data Exploration and Linear Modeling with R.

Notes

The creation of this module was funded by the National Science Foundation DBI BRC-BIO award 2217812. Cayo Santiago is supported by the Office of Research Infrastructure Programs (ORIP) of the National Institutes of Health, grant 2 P40 OD012217, and the University of Puerto Rico (UPR), Medical Sciences Campus. Additional support was provided by the National Science Foundation Graduate Research Fellowship Program to Alexis A. Diaz, award 2141410. We acknowledge the use of BioRender.com to create Fig 1.

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