Free Logistic Regression Using SAS

Author: Paul D. Allison
Edition: 2
Binding: Paperback
ISBN: 1599946416
Publisher: SAS Institute
Features:

Logistic Regression Using SAS: Theory and Application, Second Edition

If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, Paul Allison's Logistic Regression Using SAS: Theory and Application, Second Edition, 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 SAS. Search and download computer ebooks Logistic Regression Using SAS: Theory and Application, Second Edition for free.
Categories: Regression analysis->Data processing. Contributors: Paul D. Allison - Author. Format: Paperback. Download Logistic Regression Using SAS computer ebooks
Several 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 logistic regression, logit analysis of contingency tables, multinomial logit analysis, ordered logit analysis, discrete-choice analysis,

Logistic Regression Using SAS ...

Logistic Regression Using SAS SAS Publishing 9781599946412 09781599946412

Categories: Regression analysis->Data processing. Contributors: Paul D. Allison - Author. Format: Paperback

author d allison paul format paperback language english publication year 30 03 2012 subject computing it subject 2 software packages title logistic regression using sas theory and application second edition author d allison paul publisher sas publishing publication date mar 30 2012 pages 348 binding paperback edition 2 nd dimensions 8 00 wx 10 50 hx 0 75 d isbn 1599946416 subject computers mathematical statistical software description if you are a researcher or student with experience in multi

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Logistic Regression Using SAS Free

Several real-world examples are included in full detail
The following topics are covered: binary logistic regression, logit analysis of contingency tables, multinomial logit analysis, ordered logit analysis, discrete-choice analysis,