Handbook of Regression and Modeling

• Basic Statistical Concepts. Simple Linear Regression. Special Problems in Simple Linear Regression. Some Aspects and Examples in Constructing a Valid Simple Regression Study. Multiple Linear Regression. Correlation in Multiple Regression. Issues in Multiple Linear Regression. Polynomial Regression. Special Topics in Multiple Regression. Indicator (Dummy) Variable Regression. Model Building/Model Selection. Analysis of Covariance. Logistic Regression.

"Unlike many other statistical texts, Paulson's book is easy to read and comprehend. It moves the reader along the statistics learning path with much less trauma. The author takes great care to explain the logic behind the statistical analysis process as well as disclose the benefits associated with the effort. Paulson's addition of carefully selected philosophic nuggets gives certain passages of the text a delightful 'Zen' quality that is very refreshing. I enjoyed the reading experience and will use the text in my own work."- Lawton A. Seal, Healthpoint/DEB Pharmaceuticals"The author has done a commendable job of combining theory and practice. The writing is clear and supplemented with numerous worked examples. Furthermore, the clear figures and tables make the text well suited for the classroom and as a reference text for the basic scientist whose research requires regression analysis . . . I would recommend this text as a primary regression text for the applied researcher." – Gregory E. Gilbert, Medical University of South Carolina, in The American Statistician, February 2009, Vol. 63, No. 1