Mixed Models and Variance Components
Traditionally, linear models have been divided into three categories: fixed effects models, random effects models, and mixed models. The categorization depends on whether the β vector in Y = Xβ + e is fixed, random, or has both fixed and random elements. Random effects models always assume that there is a fixed overall mean for observations, so random effects models are actually mixed.
KeywordsVariance Component Orthogonal Complement Balance Incomplete Block Design Good Linear Unbiased Predictor Linear Unbiased Prediction
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