O'Reilly logo

Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS by Edward F. Vonesh

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

3

Linear Mixed-Effects Models—Normal Theory

3.1  The linear mixed-effects (LME) model

3.2  Examples

3.3  Summary

Within linear models, there are two distinct stochastic mechanisms for determining the overall correlation structure associated with repeated measurements and/or clustered data. In the marginal linear model of the preceding chapter, we account for correlation among observations from the same individual or unit by specifying a within-unit random error vector and its covariance structure. This approach assumes that random error vectors between units are independently distributed according to a multivariate normal distribution that varies between units only its dimension. In the repeated measurements setting, for example, we might ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required