Transcription of Linear Mixed Effects Models Using R - University of Michigan
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Linear Mixed Effects Models Using R - University of Michigan
Andrzej Ga leckiTomasz BurzykowskiLinear Mixed Effects ModelsUsingRA Step-by-step ApproachJanuary 31, 2012 SpringerMoim bliskimVioli, Martuni, Samancie, Arturkowi, i Pawe lkowiMoim Rodzicom i NauczycielomDekadentom najbli zszym i przyjacio lom memory of Tom Ten HavePrefaceLinear Mixed -effects model (LMMs) are powerful modeling tools that allowfor the analysis of datasets with complex, hierarchical structures. Intensive re-search in the past decade has led to a better understanding oftheir growing body of literature, including recent monographs, has consider-ably increased their popularity among applied researchers.
Linear mixed-effects model (LMMs) are powerful modeling tools that allow for the analysis of datasets with complex, hierarchical structures. Intensive re-search in the past decade has led to a better understanding of their properties. The growing body of literature, including recent monographs, has consider-
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