Applied Regression and ANOVA Using SAS

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Author :
Publisher : CRC Press
ISBN 13 : 1439869529
Total Pages : 428 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Applied Regression and ANOVA Using SAS by : Patricia F. Moodie

Download or read book Applied Regression and ANOVA Using SAS written by Patricia F. Moodie and published by CRC Press. This book was released on 2022-06-07 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Regression and ANOVA Using SAS® has been written specifically for non-statisticians and applied statisticians who are primarily interested in what their data are revealing. Interpretation of results are key throughout this intermediate-level applied statistics book. The authors introduce each method by discussing its characteristic features, reasons for its use, and its underlying assumptions. They then guide readers in applying each method by suggesting a step-by-step approach while providing annotated SAS programs to implement these steps. Those unfamiliar with SAS software will find this book helpful as SAS programming basics are covered in the first chapter. Subsequent chapters give programming details on a need-to-know basis. Experienced as well as entry-level SAS users will find the book useful in applying linear regression and ANOVA methods, as explanations of SAS statements and options chosen for specific methods are provided. Features: •Statistical concepts presented in words without matrix algebra and calculus •Numerous SAS programs, including examples which require minimum programming effort to produce high resolution publication-ready graphics •Practical advice on interpreting results in light of relatively recent views on threshold p-values, multiple testing, simultaneous confidence intervals, confounding adjustment, bootstrapping, and predictor variable selection •Suggestions of alternative approaches when a method’s ideal inference conditions are unreasonable for one’s data This book is invaluable for non-statisticians and applied statisticians who analyze and interpret real-world data. It could be used in a graduate level course for non-statistical disciplines as well as in an applied undergraduate course in statistics or biostatistics.

Regression and ANOVA: An Integrated Approach Using SAS Software + Applied Statistics: Analysis of Variance and Regression, Third Edition Set

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Author :
Publisher : Wiley-Interscience
ISBN 13 : 9780470388037
Total Pages : 0 pages
Book Rating : 4.3/5 (88 download)

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Book Synopsis Regression and ANOVA: An Integrated Approach Using SAS Software + Applied Statistics: Analysis of Variance and Regression, Third Edition Set by : Keith E. Muller

Download or read book Regression and ANOVA: An Integrated Approach Using SAS Software + Applied Statistics: Analysis of Variance and Regression, Third Edition Set written by Keith E. Muller and published by Wiley-Interscience. This book was released on 2008-03-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This set contains: 9780471469438 Regression and ANOVA: An Integrated Approach Using SAS(R) Software by Keith E. Muller, Bethel A. Fetterman and 9780471370383 Applied Statistics: Analysis of Variance and Regression, Third Edition by Ruth M. Mickey, Olive Jean Dunn, Virginia A. Clark.

Statistical Data Analysis Using SAS

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Author :
Publisher : Springer
ISBN 13 : 3319692399
Total Pages : 679 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Statistical Data Analysis Using SAS by : Mervyn G. Marasinghe

Download or read book Statistical Data Analysis Using SAS written by Mervyn G. Marasinghe and published by Springer. This book was released on 2018-04-12 with total page 679 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this textbook (previously titled SAS for Data Analytics) is to teach the use of SAS for statistical analysis of data for advanced undergraduate and graduate students in statistics, data science, and disciplines involving analyzing data. The book begins with an introduction beyond the basics of SAS, illustrated with non-trivial, real-world, worked examples. It proceeds to SAS programming and applications, SAS graphics, statistical analysis of regression models, analysis of variance models, analysis of variance with random and mixed effects models, and then takes the discussion beyond regression and analysis of variance to conclude. Pedagogically, the authors introduce theory and methodological basis topic by topic, present a problem as an application, followed by a SAS analysis of the data provided and a discussion of results. The text focuses on applied statistical problems and methods. Key features include: end of chapter exercises, downloadable SAS code and data sets, and advanced material suitable for a second course in applied statistics with every method explained using SAS analysis to illustrate a real-world problem. New to this edition: • Covers SAS v9.2 and incorporates new commands • Uses SAS ODS (output delivery system) for reproduction of tables and graphics output • Presents new commands needed to produce ODS output • All chapters rewritten for clarity • New and updated examples throughout • All SAS outputs are new and updated, including graphics • More exercises and problems • Completely new chapter on analysis of nonlinear and generalized linear models • Completely new appendix Mervyn G. Marasinghe, PhD, is Associate Professor Emeritus of Statistics at Iowa State University, where he has taught courses in statistical methods and statistical computing. Kenneth J. Koehler, PhD, is University Professor of Statistics at Iowa State University, where he teaches courses in statistical methodology at both graduate and undergraduate levels and primarily uses SAS to supplement his teaching.

SAS for Data Analysis

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 038777372X
Total Pages : 562 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis SAS for Data Analysis by : Mervyn G. Marasinghe

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.

Understanding Regression and ANOVA as Research Tools Using SAS

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Author :
Publisher : Chapman and Hall/CRC
ISBN 13 : 9781439869512
Total Pages : 384 pages
Book Rating : 4.8/5 (695 download)

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Book Synopsis Understanding Regression and ANOVA as Research Tools Using SAS by : Patricia F. Moodie

Download or read book Understanding Regression and ANOVA as Research Tools Using SAS written by Patricia F. Moodie and published by Chapman and Hall/CRC. This book was released on 2016-02-15 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed for researchers and data analysts, this book presents rigorous statistical methods without burdening readers with mathematical theory. Readers see how linear regression and ANOVA can be used in biology, agriculture, health science, environmental science, fisheries, forestry, as well as the physical, social, and behavioral sciences. Each statistical topic is illustrated using detailed worked examples and relevant SAS procedures. The book emphasizes interpretation of analyses integrating graphical and statistical results and offers a detailed step-by-step guide for each analysis.

Exploring Modern Regression Methods Using SAS

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Publisher :
ISBN 13 : 9781642954876
Total Pages : 142 pages
Book Rating : 4.9/5 (548 download)

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Book Synopsis Exploring Modern Regression Methods Using SAS by :

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.

Selected SAS Documentation

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Publisher :
ISBN 13 : 9781555449674
Total Pages : 266 pages
Book Rating : 4.4/5 (496 download)

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Book Synopsis Selected SAS Documentation by : SAS Publishing

Download or read book Selected SAS Documentation written by SAS Publishing and published by . This book was released on 1997-04-01 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Applied Regression Analysis

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 0387227539
Total Pages : 671 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Applied Regression Analysis by : John O. Rawlings

Download or read book Applied Regression Analysis written by John O. Rawlings and published by Springer Science & Business Media. This book was released on 2006-03-31 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to statistical methods and a thoeretical linear models course. Applied Regression Analysis emphasizes the concepts and the analysis of data sets. It provides a review of the key concepts in simple linear regression, matrix operations, and multiple regression. Methods and criteria for selecting regression variables and geometric interpretations are discussed. Polynomial, trigonometric, analysis of variance, nonlinear, time series, logistic, random effects, and mixed effects models are also discussed. Detailed case studies and exercises based on real data sets are used to reinforce the concepts. The data sets used in the book are available on the Internet.

Applied Regression Analysis and Other Multivariable Methods

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Publisher :
ISBN 13 : 9780534915247
Total Pages : pages
Book Rating : 4.9/5 (152 download)

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Book Synopsis Applied Regression Analysis and Other Multivariable Methods by : Kleinbaum

Download or read book Applied Regression Analysis and Other Multivariable Methods written by Kleinbaum and published by . This book was released on 1988-01-01 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Regression and ANOVA

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Author :
Publisher : SAS Press
ISBN 13 : 9781580258906
Total Pages : 0 pages
Book Rating : 4.2/5 (589 download)

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Book Synopsis Regression and ANOVA by : Keith E. Muller

Download or read book Regression and ANOVA written by Keith E. Muller and published by SAS Press. This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Muller and Fetterman (U. of N. Carolina, Chapel Hill) developed this text for use in "Intermediate Linear Models," a graduate level biostatistics class at UNC, covering basic theory, multiple regression, model building and evaluation, ANOVA, and universal tools. The text uses sets of real data, and contains almost no proofs. Ideal prerequisites for use include a matrix algebra class, an undergraduate introduction to mathematical statistics, basic programming skills in the statistical package used in the course (data input, data transformation, and analysis), and basic skills in linear models. Annotation (c)2003 Book News, Inc., Portland, OR (booknews.com).

SAS System for Regression

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 0471416649
Total Pages : 258 pages
Book Rating : 4.4/5 (714 download)

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Book Synopsis SAS System for Regression by : Rudolf Freund

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.

SAS for Linear Models

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Publisher : John Wiley & Sons
ISBN 13 : 0471221740
Total Pages : 500 pages
Book Rating : 4.4/5 (712 download)

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Book Synopsis SAS for Linear Models by : Ramon Littell

Download or read book SAS for Linear Models written by Ramon Littell and published by John Wiley & Sons. This book was released on 2002-05-24 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Features and capabilities of the REG, ANOVA, and GLM procedures are included in this introduction to analysing linear models with the SAS System. This guide shows how to apply the appropriate procedure to data analysis problems and understand PROC GLM output. Other helpful guidelines and discussions cover the following significant areas: Multivariate linear models; lack-of-fit analysis; covariance and heterogeneity of slopes; a classification with both crossed and nested effects; and analysis of variance for balanced data. This fourth edition includes updated examples, new software-related features, and new material, including a chapter on generalised linear models. Version 8 of the SAS System was used to run the SAS code examples in the book. * Provides clear explanations of how to use SAS to analyse linear models * Includes numerous SAS outputs * Includes new chapter on generalised linear models * Uses version 8 of the SAS system This book assists data analysts who use SAS/STAT software to analyse data using regression analysis and analysis of variance. It assumes familiarity with basic SAS concepts such as creating SAS data sets with the DATA step and manipulating SAS data sets with the procedures in base SAS software.

Time Series Analysis Using SAS Enterprise Guide

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Publisher : Springer Nature
ISBN 13 : 9811503214
Total Pages : 137 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Time Series Analysis Using SAS Enterprise Guide by : Timina Liu

Download or read book Time Series Analysis Using SAS Enterprise Guide written by Timina Liu and published by Springer Nature. This book was released on 2020-02-19 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to present time series analysis using the SAS Enterprise Guide software. It includes some starting background and theory to various time series analysis techniques, and demonstrates the data analysis process and the final results via step-by-step extensive illustrations of the SAS Enterprise Guide software. This book is a practical guide to time series analyses in SAS Enterprise Guide, and is valuable resource that benefits a wide variety of sectors.

Applied Regression Modeling

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Publisher : John Wiley & Sons
ISBN 13 : 1118345045
Total Pages : 319 pages
Book Rating : 4.1/5 (183 download)

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Book Synopsis Applied Regression Modeling by : Iain Pardoe

Download or read book Applied Regression Modeling written by Iain Pardoe and published by John Wiley & Sons. This book was released on 2013-01-07 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "The attention to detail is impressive. The book is very well written and the author is extremely careful with his descriptions . . . the examples are wonderful." —The American Statistician Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science, and social science applications. The author utilizes a bounty of real-life examples, case studies, illustrations, and graphics to introduce readers to the world of regression analysis using various software packages, including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear and careful writing style, the book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, and Bayesian modeling. In addition, the Second Edition features clarification and expansion of challenging topics, such as: Transformations, indicator variables, and interaction Testing model assumptions Nonconstant variance Autocorrelation Variable selection methods Model building and graphical interpretation Throughout the book, datasets and examples have been updated and additional problems are included at the end of each chapter, allowing readers to test their comprehension of the presented material. In addition, a related website features the book's datasets, presentation slides, detailed statistical software instructions, and learning resources including additional problems and instructional videos. With an intuitive approach that is not heavy on mathematical detail, Applied Regression Modeling, Second Edition is an excellent book for courses on statistical regression analysis at the upper-undergraduate and graduate level. The book also serves as a valuable resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work.

Biostatistics and Computer-based Analysis of Health Data Using SAS

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Author :
Publisher : Elsevier
ISBN 13 : 0081011717
Total Pages : 176 pages
Book Rating : 4.0/5 (81 download)

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Book Synopsis Biostatistics and Computer-based Analysis of Health Data Using SAS by : Christophe Lalanne

Download or read book Biostatistics and Computer-based Analysis of Health Data Using SAS written by Christophe Lalanne and published by Elsevier. This book was released on 2017-06-22 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research.The use of SAS for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics. This practical book is primarily intended for health researchers with a basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epidemiological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential SAS commands. Presents the use of SAS software in the statistical approach for the management of data modeling Includes elements of the language and descriptive statistics Supplies measures of association, comparison of means, and proportions for two or more samples Explores linear and logistic regression Provides survival data analysis

SAS System for Regression

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Author :
Publisher : SAS Press
ISBN 13 : 9781580257251
Total Pages : 0 pages
Book Rating : 4.2/5 (572 download)

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Book Synopsis SAS System for Regression by : Rudolf Jakob Freund

Download or read book SAS System for Regression written by Rudolf Jakob Freund and published by SAS Press. This book was released on 2000 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 include performing linear regression analyses using PROC REG and 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 SAS are assumed. The updated third edition includes revisions, updated material, and new material. You'll find information on using SAS/INSIGHT software, regression with a binary response with emphasis on PROC LOGISTIC, and nonparametric regression (smoothing) using moving averages and PROC LOESS. Additionally, updated material throughout the book includes high-resolution PROC REG graphics output, data sets by the OUTEST option described and illustrated, and using PROC SCORE to predict another data set.

Applied Logistic Regression Analysis

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Author :
Publisher : SAGE
ISBN 13 : 9780761922087
Total Pages : 130 pages
Book Rating : 4.9/5 (22 download)

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Book Synopsis Applied Logistic Regression Analysis by : Scott Menard

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.