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Author :
Publisher :
ISBN 13 : 9781642954487
Total Pages : pages
Book Rating : 4.9/5 (544 download)
Download or read book EXPLORING MODERN REGRESSION METHODS USING SAS written by and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Olga Korosteleva
Publisher : CRC Press
ISBN 13 : 1351690086
Total Pages : 325 pages
Book Rating : 4.3/5 (516 download)
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.
Author :
Publisher :
ISBN 13 : 9781642954876
Total Pages : 142 pages
Book Rating : 4.9/5 (548 download)
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.
Author : Simon Sheather
Publisher : Springer Science & Business Media
ISBN 13 : 0387096086
Total Pages : 398 pages
Book Rating : 4.3/5 (87 download)
Download or read book A Modern Approach to Regression with R written by Simon Sheather and published by Springer Science & Business Media. This book was released on 2009-02-27 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on tools and techniques for building regression models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to base inferences or conclusions only on valid models. Plots are shown to be an important tool for both building regression models and assessing their validity. We shall see that deciding what to plot and how each plot should be interpreted will be a major challenge. In order to overcome this challenge we shall need to understand the mathematical properties of the fitted regression models and associated diagnostic procedures. As such this will be an area of focus throughout the book. In particular, we shall carefully study the properties of resi- als in order to understand when patterns in residual plots provide direct information about model misspecification and when they do not. The regression output and plots that appear throughout the book have been gen- ated using R. The output from R that appears in this book has been edited in minor ways. On the book web site you will find the R code used in each example in the text.
Author : Michael Panik
Publisher : CRC Press
ISBN 13 : 1420091980
Total Pages : 830 pages
Book Rating : 4.4/5 (2 download)
Download or read book Regression Modeling written by Michael Panik and published by CRC Press. This book was released on 2009-04-30 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs. The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression, L1 and q-quantile regression, regression in a spatial domain, ridge regression, semiparametric regression, nonlinear least squares, and time-series regression issues. For most of the regression methods, the author includes SAS procedure code, enabling readers to promptly perform their own regression runs. A Comprehensive, Accessible Source on Regression Methodology and Modeling Requiring only basic knowledge of statistics and calculus, this book discusses how to use regression analysis for decision making and problem solving. It shows readers the power and diversity of regression techniques without overwhelming them with calculations.
Author : Paul D. Allison
Publisher : SAS Institute
ISBN 13 : 1629590185
Total Pages : 348 pages
Book Rating : 4.6/5 (295 download)
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.
Author : Robert N. Rodriguez
Publisher : SAS Institute
ISBN 13 : 1951684001
Total Pages : 464 pages
Book Rating : 4.9/5 (516 download)
Download or read book Building Regression Models with SAS written by Robert N. Rodriguez and published by SAS Institute. This book was released on 2023-04-18 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advance your skills in building predictive models with SAS! Building Regression Models with SAS: A Guide for Data Scientists teaches data scientists, statisticians, and other analysts who use SAS to train regression models for prediction with large, complex data. Each chapter focuses on a particular model and includes a high-level overview, followed by basic concepts, essential syntax, and examples using new procedures in both SAS/STAT and SAS Viya. By emphasizing introductory examples and interpretation of output, this book provides readers with a clear understanding of how to build the following types of models: general linear models quantile regression models logistic regression models generalized linear models generalized additive models proportional hazards regression models tree models models based on multivariate adaptive regression splines Building Regression Models with SAS is an essential guide to learning about a variety of models that provide interpretability as well as predictive performance.
Author : Paul D. Allison
Publisher :
ISBN 13 : 9781642953237
Total Pages : 160 pages
Book Rating : 4.9/5 (532 download)
Download or read book Fixed Effects Regression Methods for Longitudinal Data Using SAS written by Paul D. Allison and published by . This book was released on 2019-07-12 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fixed Effects Regression Methods for Longitudinal Data Using SAS, written by Paul Allison, is an invaluable resource for all researchers interested in adding fixed effects regression methods to their tool kit of statistical techniques. First introduced by economists, fixed effects methods are gaining widespread use throughout the social sciences. Designed to eliminate major biases from regression models with multiple observations (usually longitudinal) for each subject (usually a person), fixed effects methods essentially offer control for all stable characteristics of the subjects, even characteristics that are difficult or impossible to measure. This straightforward and thorough text shows you how to estimate fixed effects models with several SAS procedures that are appropriate for different kinds of outcome variables. The theoretical background of each model is explained, and the models are then illustrated with detailed examples using real data. The book contains thorough discussions of the following uses of SAS procedures: PROC GLM for estimating fixed effects linear models for quantitative outcomes, PROC LOGISTIC for estimating fixed effects logistic regression models, PROC PHREG for estimating fixed effects Cox regression models for repeated event data, PROC GENMOD for estimating fixed effects Poisson regression models for count data, and PROC CALIS for estimating fixed effects structural equation models. To gain the most benefit from this book, readers should be familiar with multiple linear regression, have practical experience using multiple regression on real data, and be comfortable interpreting the output from a regression analysis. An understanding of logistic regression and Poisson regression is a plus. Some experience with SAS is helpful, but not required.
Author : Andy Field
Publisher : SAGE
ISBN 13 : 1446242234
Total Pages : 753 pages
Book Rating : 4.4/5 (462 download)
Download or read book Discovering Statistics Using SAS written by Andy Field and published by SAGE. This book was released on 2010-01-30 with total page 753 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hot on the heels of the 3rd edition of Andy Field′s award-winning Discovering Statistics Using SPSS comes this brand new version for students using SAS®. Andy has teamed up with a co-author, Jeremy Miles, to adapt the book with all the most up-to-date commands and programming language from SAS® 9.2. If you′re using SAS®, this is the only book on statistics that you will need! The book provides a comprehensive collection of statistical methods, tests and procedures, covering everything you′re likely to need to know for your course, all presented in Andy′s accessible and humourous writing style. Suitable for those new to statistics as well as students on intermediate and more advanced courses, the book walks students through from basic to advanced level concepts, all the while reinforcing knowledge through the use of SAS®. A ′cast of characters′ supports the learning process throughout the book, from providing tips on how to enter data in SAS® properly to testing knowledge covered in chapters interactively, and ′real world′ and invented examples illustrate the concepts and make the techniques come alive. The book′s companion website (see link above) provides students with a wide range of invented and real published research datasets. Lecturers can find multiple choice questions and PowerPoint slides for each chapter to support their teaching.
Author : Måns Thulin
Publisher : BoD - Books on Demand
ISBN 13 : 9152701514
Total Pages : 598 pages
Book Rating : 4.1/5 (527 download)
Download or read book Modern Statistics with R written by Måns Thulin and published by BoD - Books on Demand. This book was released on 2021-07-28 with total page 598 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. The aim of Modern Statistics with R is to introduce you to key parts of the modern statistical toolkit. It teaches you: - Data wrangling - importing, formatting, reshaping, merging, and filtering data in R. - Exploratory data analysis - using visualisation and multivariate techniques to explore datasets. - Statistical inference - modern methods for testing hypotheses and computing confidence intervals. - Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting. - Simulation - using simulation techniques for sample size computations and evaluations of statistical methods. - Ethics in statistics - ethical issues and good statistical practice. - R programming - writing code that is fast, readable, and free from bugs. Starting from the very basics, Modern Statistics with R helps you learn R by working with R. Topics covered range from plotting data and writing simple R code to using cross-validation for evaluating complex predictive models and using simulation for sample size determination. The book includes more than 200 exercises with fully worked solutions. Some familiarity with basic statistical concepts, such as linear regression, is assumed. No previous programming experience is needed.
Author : Chong Ho Alex Yu
Publisher : CRC Press
ISBN 13 : 1000777790
Total Pages : 290 pages
Book Rating : 4.0/5 (7 download)
Download or read book Data Mining and Exploration written by Chong Ho Alex Yu and published by CRC Press. This book was released on 2022-10-27 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces both conceptual and procedural aspects of cutting-edge data science methods, such as dynamic data visualization, artificial neural networks, ensemble methods, and text mining. There are at least two unique elements that can set the book apart from its rivals. First, most students in social sciences, engineering, and business took at least one class in introductory statistics before learning data science. However, usually these courses do not discuss the similarities and differences between traditional statistics and modern data science; as a result learners are disoriented by this seemingly drastic paradigm shift. In reaction, some traditionalists reject data science altogether while some beginning data analysts employ data mining tools as a “black box”, without a comprehensive view of the foundational differences between traditional and modern methods (e.g., dichotomous thinking vs. pattern recognition, confirmation vs. exploration, single method vs. triangulation, single sample vs. cross-validation etc.). This book delineates the transition between classical methods and data science (e.g. from p value to Log Worth, from resampling to ensemble methods, from content analysis to text mining etc.). Second, this book aims to widen the learner's horizon by covering a plethora of software tools. When a technician has a hammer, every problem seems to be a nail. By the same token, many textbooks focus on a single software package only, and consequently the learner tends to fit the problem with the tool, but not the other way around. To rectify the situation, a competent analyst should be equipped with a tool set, rather than a single tool. For example, when the analyst works with crucial data in a highly regulated industry, such as pharmaceutical and banking, commercial software modules (e.g., SAS) are indispensable. For a mid-size and small company, open-source packages such as Python would come in handy. If the research goal is to create an executive summary quickly, the logical choice is rapid model comparison. If the analyst would like to explore the data by asking what-if questions, then dynamic graphing in JMP Pro is a better option. This book uses concrete examples to explain the pros and cons of various software applications.
Author : Geoff Der
Publisher : CRC Press
ISBN 13 : 1439867976
Total Pages : 562 pages
Book Rating : 4.4/5 (398 download)
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 562 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, longitudinal and survival data analysis, missing data, generalized additive models (GAMs), and Bayesian methods. The book focuses on performing these analyses using SAS, the software package of choice for those analysing medical data. Features Covers the planning stage of medical studies in detail; several chapters contain details of sample size estimation Illustrates methods of randomisation that might be employed for clinical trials Covers topics that have become of great importance in the 21st century, including Bayesian methods and multiple imputation Its breadth and depth, coupled with the inclusion of all the SAS code, make this book ideal for practitioners as well as for a graduate class in biostatistics or public health. Complete data sets, all the SAS code, and complete outputs can be found on an associated website: http://support.sas.com/amsus
Author : Daryl S. Paulson
Publisher : CRC Press
ISBN 13 : 1420017381
Total Pages : 520 pages
Book Rating : 4.4/5 (2 download)
Download or read book Handbook of Regression and Modeling written by Daryl S. Paulson and published by CRC Press. This book was released on 2006-12-19 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Carefully designed for use by clinical and pharmaceutical researchers and scientists, Handbook of Regression Analysis and Modeling explores statistical methods that have been adapted into biological applications for the quickly evolving field of biostatistics. The author clearly delineates a six-step method for hypothesis testing using data that mimics real life. Relying heavily on computer software, he includes exploratory data analysis to evaluate the fit of the model to the actual data. The book presents a well-defined procedure for adding or subtracting independent variables to the model variable and covers how to apply statistical forecasting methods to the serially correlated data characteristically found in clinical and pharmaceutical settings. The stand alone chapters allow you to pick and choose which chapter to read first and home in on the information that fits your immediate needs. Each example is presented in computer software format. The author uses MINITAB in the book but supplies instructions for SAS and SPSSX, making the book easily adaptable to individual situations. Although written with the assumption that the reader has knowledge of basic and matrix algebra, the book supplies a short course on matrix algebra in the appendix for those who need it. Covering more than just statistical theory, the book provides advanced methods that you can put to immediate use.
Author : Leonard C. Onyiah
Publisher : CRC Press
ISBN 13 : 1420060554
Total Pages : 852 pages
Book Rating : 4.4/5 (2 download)
Download or read book Design and Analysis of Experiments written by Leonard C. Onyiah and published by CRC Press. This book was released on 2008-07-29 with total page 852 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlike other books on the modeling and analysis of experimental data, Design and Analysis of Experiments: Classical and Regression Approaches with SAS not only covers classical experimental design theory, it also explores regression approaches. Capitalizing on the availability of cutting-edge software, the author uses both manual meth
Author : Rudolf Freund
Publisher : John Wiley & Sons
ISBN 13 : 0471416649
Total Pages : 258 pages
Book Rating : 4.4/5 (714 download)
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.
Author : David Diez
Publisher :
ISBN 13 : 9781943450046
Total Pages : pages
Book Rating : 4.4/5 (5 download)
Download or read book OpenIntro Statistics written by David Diez and published by . This book was released on 2015-07-02 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.
Author : Olga Korosteleva
Publisher : CRC Press
ISBN 13 : 1351690078
Total Pages : 273 pages
Book Rating : 4.3/5 (516 download)
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 273 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.
