Normal-Theory Methods: Linear Mixed Models

Part of the Springer Texts in Statistics book series (STS)


Chapters 3, 4, and 5 have considered the situation in which a normally distributed outcome variable is measured repeatedly from each subject or experimental unit. The analysis of such data must account for the dependence among a subject’s multiple measurements. “Classical” methodology is based either on multivariate normal models with general covariance structure (Chapters 3 and 4) or on univariate repeated measures ANOVA (Chapter 5). In practice, however, repeated measurements studies are characterized by:
  • variation among experimental units with respect to the number andtiming of observations;

  • missing data;

  • •|time-dependent covariates.


Linear Mixed Model Bayesian Information Criterion Covariance Structure Covariance Model Cervical Dystonia 
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© Springer-Verlag New York, Inc. 2002

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