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Methods Based on Extensions of Generalized Linear Models

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

Abstract

In many applications in which the response variable of interest has a continuous distribution, the normal-theory methods described in Chapters 3–6 may be inappropriate. In addition, in situations where the response variable is categorical, the WLS (Chapter 7) and randomization model (Chapter 8) approaches are not always applicable. For example, although the WLS methodology is often a useful approach to the analysis of repeated binary and ordered categorical outcome variables, it can only accommodate categorical explanatory variables. In addition, the WLS methodology requires a sufficiently large sample size for the marginal response functions at each time point within each subpopulation from the multiway cross-classification of the explanatory variables to have an approximately multivariate normal distribution. The randomization model approach is useful only in one-sample problems. Thus, neither of these methodologies for categorical outcomes can be used in the general repeated measurements setting.

Keywords

Generalize Linear Model Botulinum Toxin Generalize Estimate Equation Marginal Model Spasmodic Torticollis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York, Inc. 2002

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