Generalized linear models : with applications in engineering & the sciences

This volume serves as an introductory text or reference on generalized linear models. The range of theoretical topics and applications give this book broad appeal to practicing professionals in a variety of fields and as a textbook for students in regression courses. Includes thorough treatment of logistic and Poisson regression. l Introduction to generalised estimating questions l Numerous examples in fields ranging from biology and biopharmaceuticals to engineering and quality assurance l Provides guidance in using widely available software to illustrate all aspects of model-fitting, inference, and diagnostic testing

Preface.

1. Introduction to Generalized Linear Models.

2. Linear Regression Models.

3. Nonlinear Regression Models.

4. Logistic and Poisson Regression Models.

5. The Family of Generalized Linear Models.

6. Generalized Estimating Equations.

7. Further Advances and Applications in GLM.

Appendix 1: Background on Basic Test Statistics.

Appendix 2: Background from the Theory of Linear Models.

Appendix 3: The Gauss Markov Theroem.

Appendix 4: The Relationship Between Maximum Likelihood Estimation of the Logistic Regression Model and Weighted Least Squares.

Appendix 5: Computational Details for GLMs for a Canonical Link.

Appendix 6: Computational Details for GLMs for a Noncanonical Link.

References.

Index.