Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS
This reference explores generalized linear and nonlinear models for correlated data, connecting statistical theory with applications using SAS. It is suited to readers studying advanced data analysis and modeling methods where observations are related, and offers a focused resource centered on both methodology and practical implementation.
About This Book
Generalized Linear and Nonlinear Models for Correlated Data addresses statistical modeling when observations are related rather than independent.
The book brings together theory and applications involving generalized linear and nonlinear models.
SAS is used as the application environment, making the title relevant to readers seeking a practical connection between statistical methods and software-based analysis.
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