Download or read book Logistic Regression Using SAS written by Paul D. Allison and published by SAS Institute. This book was released on 2012-03-30 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Includes several real-world examples in full detail.

Download or read book SAS System for Regression written by Rudolf Freund and published by John Wiley & Sons. This book was released on 2000-12-29 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: SAS® System for Regression Learn to perform a wide variety of regression analyses using SAS® software with this example-driven revised favorite from SAS Publishing. With this Third Edition you will learn the basics of performing regression analyses using a wide variety of models including nonlinear models. Other topics covered include performing linear regression analyses using PROC REG diagnosing and providing remedies for data problems, including outliers and multicollinearity. Examples feature numerous SAS procedures including REG, PLOT, GPLOT, NLIN, RSREG, AUTOREG, PRINCOMP, and others. A helpful discussion of theory is supplied where necessary. Some knowledge of both regression and the SAS System are assumed. New for this edition The Third Edition includes revisions, updated material, and new material. You’ll find new information on using SAS/INSIGHT® software regression with a binary response with emphasis on PROC LOGISTIC nonparametric regression (smoothing) using moving averages and PROC LOESS. Additionally, updated material throughout the book includes high-resolution PROC REG graphics output, using the OUTEST option to produce a data set, and using PROC SCORE to predict another data set.

Download or read book Logistic Regression Using the SAS System written by Paul D. Allison and published by Wiley-SAS. This book was released on 2001-12-21 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in an informal and non-technical style, this book first explains the theory behind logistic regression and then shows how to implement it using the SAS System. Allison includes several detailed, real-world examples of the social sciences to provide readers with a better understanding of the material. He also explores the differences and similarities among the many generalizations of the logistic regression model.

Download or read book Applied Econometrics Using the SAS System written by Vivek Ajmani and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first cutting-edge guide to using the SAS® system for the analysis of econometric data Applied Econometrics Using the SAS® System is the first book of its kind to treat the analysis of basic econometric data using SAS®, one of the most commonly used software tools among today's statisticians in business and industry. This book thoroughly examines econometric methods and discusses how data collected in economic studies can easily be analyzed using the SAS® system. In addition to addressing the computational aspects of econometric data analysis, the author provides a statistical foundation by introducing the underlying theory behind each method before delving into the related SAS® routines. The book begins with a basic introduction to econometrics and the relationship between classical regression analysis models and econometric models. Subsequent chapters balance essential concepts with SAS® tools and cover key topics such as: Regression analysis using Proc IML and Proc Reg Hypothesis testing Instrumental variables analysis, with a discussion of measurement errors, the assumptions incorporated into the analysis, and specification tests Heteroscedasticity, including GLS and FGLS estimation, group-wise heteroscedasticity, and GARCH models Panel data analysis Discrete choice models, along with coverage of binary choice models and Poisson regression Duration analysis models Assuming only a working knowledge of SAS®, this book is a one-stop reference for using the software to analyze econometric data. Additional features include complete SAS® code, Proc IML routines plus a tutorial on Proc IML, and an appendix with additional programs and data sets. Applied Econometrics Using the SAS® System serves as a relevant and valuable reference for practitioners in the fields of business, economics, and finance. In addition, most students of econometrics are taught using GAUSS and STATA, yet SAS® is the standard in the working world; therefore, this book is an ideal supplement for upper-undergraduate and graduate courses in statistics, economics, and other social sciences since it prepares readers for real-world careers.

Download or read book Applied Logistic Regression Analysis written by Scott Menard and published by SAGE. This book was released on 2002 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Complex Survey Data Analysis with SAS written by Taylor H. Lewis and published by CRC Press. This book was released on 2016-09-15 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex Survey Data Analysis with SAS® is an invaluable resource for applied researchers analyzing data generated from a sample design involving any combination of stratification, clustering, unequal weights, or finite population correction factors. After clearly explaining how the presence of these features can invalidate the assumptions underlying most traditional statistical techniques, this book equips readers with the knowledge to confidently account for them during the estimation and inference process by employing the SURVEY family of SAS/STAT® procedures. The book offers comprehensive coverage of the most essential topics, including: Drawing random samples Descriptive statistics for continuous and categorical variables Fitting and interpreting linear and logistic regression models Survival analysis Domain estimation Replication variance estimation methods Weight adjustment and imputation methods for handling missing data The easy-to-follow examples are drawn from real-world survey data sets spanning multiple disciplines, all of which can be downloaded for free along with syntax files from the author’s website: http://mason.gmu.edu/~tlewis18/. While other books may touch on some of the same issues and nuances of complex survey data analysis, none features SAS exclusively and as exhaustively. Another unique aspect of this book is its abundance of handy workarounds for certain techniques not yet supported as of SAS Version 9.4, such as the ratio estimator for a total and the bootstrap for variance estimation. Taylor H. Lewis is a PhD graduate of the Joint Program in Survey Methodology at the University of Maryland, College Park, and an adjunct professor in the George Mason University Department of Statistics. An avid SAS user for 15 years, he is a SAS Certified Advanced programmer and a nationally recognized SAS educator who has produced dozens of papers and workshops illustrating how to efficiently and effectively conduct statistical analyses using SAS.

Download or read book Categorical Data Analysis Using SAS Third Edition written by Maura E. Stokes and published by SAS Institute. This book was released on 2012-07-31 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statisticians and researchers will find this book, newly updated for SAS/STAT 12.1, to be a useful discussion of categorical data analysis techniques as well as an invaluable aid in applying these methods with SAS.

Download or read book Regression Analysis by Example written by Samprit Chatterjee and published by John Wiley & Sons. This book was released on 2015-02-25 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Fourth Edition: "This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable." —Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded and thoroughly updated to reflect recent advances in the field. The emphasis continues to be on exploratory data analysis rather than statistical theory. The book offers in-depth treatment of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression. The book now includes a new chapter on the detection and correction of multicollinearity, while also showcasing the use of the discussed methods on newly added data sets from the fields of engineering, medicine, and business. The Fifth Edition also explores additional topics, including: Surrogate ridge regression Fitting nonlinear models Errors in variables ANOVA for designed experiments Methods of regression analysis are clearly demonstrated, and examples containing the types of irregularities commonly encountered in the real world are provided. Each example isolates one or two techniques and features detailed discussions, the required assumptions, and the evaluated success of each technique. Additionally, methods described throughout the book can be carried out with most of the currently available statistical software packages, such as the software package R. Regression Analysis by Example, Fifth Edition is suitable for anyone with an understanding of elementary statistics.

Download or read book Logistic Regression Using SAS written by Paul D. Allison and published by SAS Institute. This book was released on 2012-03-30 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Logistic Regression written by Scott W. Menard and published by SAGE. This book was released on 2010 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book SAS for Data Analysis written by Mervyn G. Marasinghe and published by Springer Science & Business Media. This book was released on 2008-12-10 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate majors or advanced undergraduate students from a variety of disciplines. These students typically have taken an introductory-level s- tistical methods course that requires the use a software system such as SAS for performing statistical analysis. Thus students are expected to have an - derstanding of basic concepts of statistical inference such as estimation and hypothesis testing. Understandably, adequate time is not available in a ?rst course in stat- tical methods to cover the use of a software system adequately in the amount of time available for instruction. The aim of this book is to teach how to use the SAS system for data analysis. The SAS language is introduced at a level of sophistication not found in most introductory SAS books. Important features such as SAS data step programming, pointers, and line-hold spe- ?ers are described in detail. The powerful graphics support available in SAS is emphasized throughout, and many worked SAS program examples contain graphic components.

Download or read book Advanced Regression Models with SAS and R written by Olga Korosteleva and published by CRC Press. This book was released on 2018-12-07 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Regression Models with SAS and R exposes the reader to the modern world of regression analysis. The material covered by this book consists of regression models that go beyond linear regression, including models for right-skewed, categorical and hierarchical observations. The book presents the theory as well as fully worked-out numerical examples with complete SAS and R codes for each regression. The emphasis is on model accuracy and the interpretation of results. For each regression, the fitted model is presented along with interpretation of estimated regression coefficients and prediction of response for given values of predictors. Features: Presents the theoretical framework for each regression. Discusses data that are categorical, count, proportions, right-skewed, longitudinal and hierarchical. Uses examples based on real-life consulting projects. Provides complete SAS and R codes for each example. Includes several exercises for every regression. Advanced Regression Models with SAS and R is designed as a text for an upper division undergraduate or a graduate course in regression analysis. Prior exposure to the two software packages is desired but not required. The Author: Olga Korosteleva is a Professor of Statistics at California State University, Long Beach. She teaches a large variety of statistical courses to undergraduate and master’s students. She has published three statistical textbooks. For a number of years, she has held the position of faculty director of the statistical consulting group. Her research interests lie mostly in applications of statistical methodology through collaboration with her clients in health sciences, nursing, kinesiology, and other fields.

Download or read book Exploring Modern Regression Methods Using SAS written by and published by . This book was released on 2019-06-21 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: This special collection of SAS Global Forum papers demonstrates new and enhanced capabilities and applications of lesser-known SAS/STAT and SAS Viya procedures for regression models. The goal here is to raise awareness of current valuable SAS/STAT content of which the user may not be aware. Also available free as a PDF from sas.com/books.

Download or read book Practical Guide to Logistic Regression written by Joseph M. Hilbe and published by CRC Press. This book was released on 2016-04-05 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Guide to Logistic Regression covers the key points of the basic logistic regression model and illustrates how to use it properly to model a binary response variable. This powerful methodology can be used to analyze data from various fields, including medical and health outcomes research, business analytics and data science, ecology, fishe

Download or read book Applied Medical Statistics Using SAS written by Geoff Der and published by CRC Press. This book was released on 2012-10-01 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written with medical statisticians and medical researchers in mind, this intermediate-level reference explores the use of SAS for analyzing medical data. Applied Medical Statistics Using SAS covers the whole range of modern statistical methods used in the analysis of medical data, including regression, analysis of variance and covariance, longitudi

Download or read book A Handbook of Statistical Graphics Using SAS ODS written by Geoff Der and published by CRC Press. This book was released on 2014-08-15 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Easily Use SAS to Produce Your Graphics Diagrams, plots, and other types of graphics are indispensable components in nearly all phases of statistical analysis, from the initial assessment of the data to the selection of appropriate statistical models to the diagnosis of the chosen models once they have been fitted to the data. Harnessing the full graphics capabilities of SAS, A Handbook of Statistical Graphics Using SAS ODS covers essential graphical methods needed in every statistician’s toolkit. It explains how to implement the methods using SAS 9.4. The handbook shows how to use SAS to create many types of statistical graphics for exploring data and diagnosing fitted models. It uses SAS’s newer ODS graphics throughout as this system offers a number of advantages, including ease of use, high quality of results, consistent appearance, and convenient semiautomatic graphs from the statistical procedures. Each chapter deals graphically with several sets of example data from a wide variety of areas, such as epidemiology, medicine, and psychology. These examples illustrate the use of graphic displays to give an overview of data, to suggest possible hypotheses for testing new data, and to interpret fitted statistical models. The SAS programs and data sets are available online.

Download or read book Categorical Data Analysis written by Alan Agresti and published by John Wiley & Sons. This book was released on 2013-04-08 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Second Edition "A must-have book for anyone expecting to do research and/or applications in categorical data analysis." —Statistics in Medicine "It is a total delight reading this book." —Pharmaceutical Research "If you do any analysis of categorical data, this is an essential desktop reference." —Technometrics The use of statistical methods for analyzing categorical data has increased dramatically, particularly in the biomedical, social sciences, and financial industries. Responding to new developments, this book offers a comprehensive treatment of the most important methods for categorical data analysis. Categorical Data Analysis, Third Edition summarizes the latest methods for univariate and correlated multivariate categorical responses. Readers will find a unified generalized linear models approach that connects logistic regression and Poisson and negative binomial loglinear models for discrete data with normal regression for continuous data. This edition also features: An emphasis on logistic and probit regression methods for binary, ordinal, and nominal responses for independent observations and for clustered data with marginal models and random effects models Two new chapters on alternative methods for binary response data, including smoothing and regularization methods, classification methods such as linear discriminant analysis and classification trees, and cluster analysis New sections introducing the Bayesian approach for methods in that chapter More than 100 analyses of data sets and over 600 exercises Notes at the end of each chapter that provide references to recent research and topics not covered in the text, linked to a bibliography of more than 1,200 sources A supplementary website showing how to use R and SAS; for all examples in the text, with information also about SPSS and Stata and with exercise solutions Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and methodologists, such as biostatisticians and researchers in the social and behavioral sciences, medicine and public health, marketing, education, finance, biological and agricultural sciences, and industrial quality control.