Analysis of Mixed Models Data
Spring 2023
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Ken KleinmanDescription
Integration of linear models with experimental design and sampling, considering applications with unbalanced and missing data. In-depth discussion of mixed models including parameterizations, analysis of covariance, unequal numbers of observations per cell, missing cells. Repeated measure designs and longitudinal data analysis emphasized, with many examples illustrated using SAS. Prerequisite: BIOST&EP 640 and 691F or equivalent. Recommended: Bioepi 741 and 744.
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