Abstract
Many common statistical models can be expressed as linear models that incorporate both fixed effects, which are parameters associated with an entire population or with certain repeatable levels of experimental factors, and random effects, which are associated with individual experimental units drawn at random from a population. A model with both fixed effects and random effects is called a mixed-effects model.
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(2000). Linear Mixed-Effects Models: Basic Concepts and Examples. In: Mixed-Effects Models in Sand S-PLUS. Statistics and Computing. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0318-1_1
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DOI: https://doi.org/10.1007/978-1-4419-0318-1_1
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-0317-4
Online ISBN: 978-1-4419-0318-1
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