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Starts with the history of analysis of variance and continues with discussions of balanced data, analysis of variance for unbalanced data, predictions of random variables, hierarchical models and bayesian estimation, binary and discrete data, and the dispersion mean model.
History and comment; the 1-way classification; balanced data; analysis of variance estimation for unbalanced data; maximum likelihood (ML) and restricted maximum likelihood (REML); prediction of random variables; computing ML and REML estimates; hierarchical models and Bayesian estimation; binary and discrete data; other procedures; the dispersion-mean model.
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