Ruby Programming for the Absolute Beginner or Logistic Regression Using the SAS System

Ruby Programming for the Absolute Beginner

Author: Jerry Lee Ford

Want to learn the fundamentals of Ruby programming but aren't sure where to start? Look no further! Ruby is a free, easy-to-learn, yet powerful scripting programming language that can run on any operating system. These attributes have made Ruby an extremely popular language in recent years for almost any programming task. Ruby Programming for the Absolute Beginner teaches you the basics of computer programming with Ruby through the creation of simple computer games. Not only will this "learn by doing" approach provide you with an instant sense of accomplishment, but it's also a fun way to learn. In addition to learning Ruby, you'll also learn the basics of computer programming, so you'll have a solid foundation from which you can confidently jump to other programming languages.

Interesting book: Still Going Strong or Antipasto Table

Logistic Regression Using the SAS System: Theory and Application

Author: Paul D Allison

If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, this book is for you! Informal and nontechnical, this book both explains the theory behind logistic regression and looks at all the practical details involved in its implementation using the SAS System. Several social science real-world examples are included in full detail. This book also explains the differences and similarities among the many generalizations of the logistic regression model. The following topics are covered: binary logit analysis, logit analysis of contingency tables, multinomial logit analysis, ordered logit analysis, discrete-choice analysis with the PHREG procedure, and Poisson regression. Other highlights include discussions on how to use the GENMOD procedure to do loglinear analysis and GEE estimation for longitudinal binary data. Only basic knowledge of the SAS DATA step is assumed. Supports releases 6.12 and higher of SAS software.

Table of Contents:

	Acknowledgments
Ch. 1	Introduction	1
Ch. 2	Binary Logit Analysis: Basics	5
Ch. 3	Binary Logit Analysis: Details and Options	31
Ch. 4	Logit Analysis of Contingency Tables	81
Ch. 5	Multinomial Logit Analysis	111
Ch. 6	Logit Analysis for Ordered Categories	133
Ch. 7	Discrete Choice Analysis	161
Ch. 8	Logit Analysis of Longitudinal and Other Clustered Data	179
Ch. 9	Poisson Regression	217
Ch. 10	Loglinear Analysis of Contingency Tables	233
	Appendix	267
	References	275
	Index	279