Logistic Regression Using The Sas System
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Logistic Regression Using Sas
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Author : Paul D. Allison
language : en
Publisher: SAS Institute
Release Date : 2012-03-30
Logistic Regression Using Sas written by Paul D. Allison and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-30 with Computers categories.
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. 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, 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. The second edition describes many new features of PROC LOGISTIC, including conditional logistic regression, exact logistic regression, generalized logit models, ROC curves, the ODDSRATIO statement (for analyzing interactions), and the EFFECTPLOT statement (for graphing nonlinear effects). Also new is coverage of PROC SURVEYLOGISTIC (for complex samples), PROC GLIMMIX (for generalized linear mixed models), PROC QLIM (for selection models and heterogeneous logit models), and PROC MDC (for advanced discrete choice models). This book is part of the SAS Press program.
Logistic Regression Using The Sas System
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Author : Paul D. Allison
language : en
Publisher: Wiley-Interscience
Release Date : 2008-03-14
Logistic Regression Using The Sas System written by Paul D. Allison and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-14 with Mathematics categories.
This set contains: 9780471221753 Logistic Regression Using the SAS System: Theory and Application by Paul D. Allison and 9780471746966 Regression Analysis by Example, Fourth Edition by Samprit Chatterjee, Ali S. Hadi.
Logistic Regression Using The Sas System
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Author : Paul D. Allison
language : en
Publisher:
Release Date : 2000
Logistic Regression Using The Sas System written by Paul D. Allison and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.
Logistic Regression Examples Using The Sas System
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Author : SAS Institute
language : en
Publisher: Sas Inst
Release Date : 1995
Logistic Regression Examples Using The Sas System written by SAS Institute and has been published by Sas Inst this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.
Data set examples show how to create a SAS data set for the raw data and print the data set.
Logistic Regression
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Author : Scott W. Menard
language : en
Publisher: SAGE
Release Date : 2010
Logistic Regression written by Scott W. Menard and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Mathematics categories.
Logistic Regression is designed for readers who have a background in statistics at least up to multiple linear regression, who want to analyze dichotomous, nominal, and ordinal dependent variables cross-sectionally and longitudinally.
Logistic Regression Models For Ordinal Response Variables
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Author : Ann A. O'Connell
language : en
Publisher: SAGE
Release Date : 2006
Logistic Regression Models For Ordinal Response Variables written by Ann A. O'Connell and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Mathematics categories.
Ordinal measures provide a simple and convenient way to distinguish among possible outcomes. The book provides practical guidance on using ordinal outcome models.
Data Mining Using Sas Applications
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Author : George Fernandez
language : en
Publisher: CRC Press
Release Date : 2010-12-12
Data Mining Using Sas Applications written by George Fernandez and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-12-12 with Business & Economics categories.
Most books on data mining focus on principles and furnish few instructions on how to carry out a data mining project. Data Mining Using SAS Applications not only introduces the key concepts but also enables readers to understand and successfully apply data mining methods using powerful yet user-friendly SAS macro-call files. These methods stress the use of visualization to thoroughly study the structure of data and check the validity of statistical models fitted to data. Learn how to convert PC databases to SAS data Discover sampling techniques to create training and validation samples Understand frequency data analysis for categorical data Explore supervised and unsupervised learning Master exploratory graphical techniques Acquire model validation techniques in regression and classification The text furnishes 13 easy-to-use SAS data mining macros designed to work with the standard SAS modules. No additional modules or previous experience in SAS programming is required. The author shows how to perform complete predictive modeling, including data exploration, model fitting, assumption checks, validation, and scoring new data, on SAS datasets in less than ten minutes!
Interaction Effects In Logistic Regression
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Author : James Jaccard
language : en
Publisher: SAGE
Release Date : 2001-02-21
Interaction Effects In Logistic Regression written by James Jaccard and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-02-21 with Mathematics categories.
This work introduces general strategies for testing interactions in logistic regression as well as providing the tools to interpret and understand the meaning of coefficients in equations with product terms.
Applied Ordinal Logistic Regression Using Stata
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Author : Xing Liu
language : en
Publisher: SAGE Publications
Release Date : 2015-09-30
Applied Ordinal Logistic Regression Using Stata written by Xing Liu and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-30 with Social Science categories.
The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata by Xing Liu helps readers learn how to conduct analyses, interpret the results from Stata output, and present those results in scholarly writing. Using step-by-step instructions, this non-technical, applied book leads students, applied researchers, and practitioners to a deeper understanding of statistical concepts by closely connecting the underlying theories of models with the application of real-world data using statistical software.
Applied Logistic Regression Analysis
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Author : Scott Menard
language : en
Publisher: SAGE
Release Date : 2002
Applied Logistic Regression Analysis written by Scott Menard and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Mathematics categories.
The focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. The book includes detailed discussions of goodness of fit, indices of predictive efficiency, and standardized logistic regression coefficients, and examples using SAS and SPSS are included. More detailed consideration of grouped as opposed to case-wise data throughout the book Updated discussion of the properties and appropriate use of goodness of fit measures, R-square analogues, and indices of predictive efficiency Discussion of the misuse of odds ratios to represent risk ratios, and of over-dispersion and under-dispersion for grouped data Updated coverage of unordered and ordered polytomous logistic regression models.