Abstract
The models considered in all of the previous chapters contain only one random element, the random error. Many situations call for models in which there is more than one random term. This chapter introduces mixed models that contain both fixed effects and several random effects. Analysis of variance models for randomized block designs and split-plot experiments and models for repeated measurement data are special cases of mixed effects models. Hypothesis testing based on generalized least squares (GLS), maximum likelihood (ML), and restricted maximum likelihood (REML) are discussed.
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© 1998 Springer-Verlag New York, Inc.
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(1998). Mixed Effects Models. In: Rawlings, J.O., Pantula, S.G., Dickey, D.A. (eds) Applied Regression Analysis. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/0-387-22753-9_18
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DOI: https://doi.org/10.1007/0-387-22753-9_18
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-98454-4
Online ISBN: 978-0-387-22753-5
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