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During the past 25 years, mixed models have become an integral part of statistical methodology. Nearly all areas of application that use statistics use mixed models in some form. Mixed models are taught in graduate-level statistics courses, as well as disciplines outside traditional statistics. Mixed models are familiar to most statisticians. Nonetheless, many persons who are engaged in analyzing mixed model data have questions about the appropriate implementation of the methodology. In addition, given the rapid growth of degree programs in data science, as well as statistics, those who are new to the discipline and ready to extend their knowledge of statistical methods to mixed models need a place ...
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