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

4

Generalized Linear and Nonlinear Models

4.1  The generalized linear model (GLIM)

4.2  The GLIM for correlated response data

4.3  Examples of GLIM's

4.4  The generalized nonlinear model (GNLM)

4.5  Examples of GNLM's

4.6  Computational considerations

4.7  Summary

While normal-theory linear models find a wide range of use, there are numerous applications where the data are non-Gaussian in nature and, as such, involve distributions where the mean response is likely to be nonlinear in the parameters of interest. In Chapter 1 we considered several such examples including the respiratory disorder data involving repeated binary outcomes over time and the epileptic seizure data in which the primary outcome was a count of the number of epileptic ...

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