Exploring Modern Regression Methods Using Sas

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Exploring Modern Regression Methods Using Sas

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Author :
language : en
Publisher:
Release Date : 2019

Exploring Modern Regression Methods Using Sas written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Research categories.

Discovering Statistics Using Sas

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Author : Andy Field
language : en
Publisher: SAGE
Release Date : 2010-01-30

Discovering Statistics Using Sas written by Andy Field and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-30 with Reference categories.

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.

Data Mining And Exploration

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Author : Chong Ho Alex Yu
language : en
Publisher: CRC Press
Release Date : 2022-10-27

Data Mining And Exploration written by Chong Ho Alex Yu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-27 with Business & Economics categories.

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.

Regression Linear Modeling

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Author : Jason W. Osborne
language : en
Publisher: SAGE Publications
Release Date : 2016-03-24

Regression Linear Modeling written by Jason W. Osborne and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-24 with Psychology categories.

In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. The author returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.

Hierarchical Linear Modeling

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Author : G. David Garson
language : en
Publisher: SAGE
Release Date : 2013

Hierarchical Linear Modeling written by G. David Garson and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Mathematics categories.

This book provides a brief, easy-to-read guide to implementing hierarchical linear modeling using three leading software platforms, followed by a set of original how-to applications articles following a standardard instructional format. The "guide" portion consists of five chapters by the editor, providing an overview of HLM, discussion of methodological assumptions, and parallel worked model examples in SPSS, SAS, and HLM software. The "applications" portion consists of ten contributions in which authors provide step by step presentations of how HLM is implemented and reported for introductory to intermediate applications.

Modern Regression Techniques Using R

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Author : Daniel B Wright
language : en
Publisher: SAGE
Release Date : 2009-02-19

Modern Regression Techniques Using R written by Daniel B Wright and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-02-19 with Mathematics categories.

Statistics is the language of modern empirical social and behavioural science and the varieties of regression form the basis of this language. Statistical and computing advances have led to new and exciting regressions that have become the necessary tools for any researcher in these fields. In a way that is refreshingly engaging and readable, Wright and London describe the most useful of these techniques and provide step-by-step instructions, using the freeware R, to analyze datasets that can be located on the books′ webpage: www.sagepub.co.uk/wrightandlondon. Techniques covered in this book include multilevel modeling, ANOVA and ANCOVA, path analysis, mediation and moderation, logistic regression (generalized linear models), generalized additive models, and robust methods. These are all tested out using a range of real research examples conducted by the authors in every chapter. Given the wide coverage of techniques, this book will be essential reading for any advanced undergraduate and graduate student (particularly in psychology) and for more experienced researchers wanting to learn how to apply some of the more recent statistical techniques to their datasets. The Authors are donating all royalties from the book to the American Partnership for Eosinophilic Disorders.

Applied Medical Statistics Using Sas

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Author : Geoff Der
language : en
Publisher: CRC Press
Release Date : 2012-10-01

Applied Medical Statistics Using Sas written by Geoff Der and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-01 with Mathematics categories.

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

Sas For Linear Models

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Author : Ramon Littell
language : en
Publisher: John Wiley & Sons
Release Date : 2002-05-24

Sas For Linear Models written by Ramon Littell and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-05-24 with Mathematics categories.

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.

Biostatistics A Computing Approach

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Author : Stewart Anderson
language : en
Publisher: CRC Press
Release Date : 2011-12-20

Biostatistics A Computing Approach written by Stewart Anderson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-20 with Mathematics categories.

The emergence of high-speed computing has facilitated the development of many exciting statistical and mathematical methods in the last 25 years, broadening the landscape of available tools in statistical investigations of complex data. Biostatistics: A Computing Approach focuses on visualization and computational approaches associated with both mo

A Modern Approach To Regression With R

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Author : Simon Sheather
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-02-27

A Modern Approach To Regression With R written by Simon Sheather and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-02-27 with Mathematics categories.

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.