Handbook of Statistical Analyses Using Stata, Fourth Edition PDF Download

Author: Brian S. Everitt
Publisher: CRC Press
ISBN: 9781584887560
Category : Mathematics
Languages : en
Pages : 364

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Book Description
With each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. Fulfilling this need, A Handbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9. This edition covers many new features of Stata, including a new command for mixed models and a new matrix language. Each chapter describes the analysis appropriate for a particular application, focusing on the medical, social, and behavioral fields. The authors begin each chapter with descriptions of the data and the statistical techniques to be used. The methods covered include descriptives, simple tests, variance analysis, multiple linear regression, logistic regression, generalized linear models, survival analysis, random effects models, and cluster analysis. The core of the book centers on how to use Stata to perform analyses and how to interpret the results. The chapters conclude with several exercises based on data sets from different disciplines. A concise guide to the latest version of Stata, A Handbook of Statistical Analyses Using Stata, Fourth Edition illustrates the benefits of using Stata to perform various statistical analyses for both data analysis courses and self-study.

Author: Sophia Rabe-Hesketh
Publisher: Chapman and Hall/CRC
ISBN:
Category : Computers
Languages : en
Pages : 236

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Book Description
This handbook describes the features of Stata - an exciting statistical package used for standard and non-standard methods of data analysis. A Handbook of Statistical Analyses Using Stata shows outlines this package's usefulness in: modeling complex data from longitudinal studies or surveys analyzing results from clinical trials or epidemiological studies enabling tailor-made analyses with its powerful programming language Each chapter identifies the appropriate analysis for a particular set of data. A brief account of statistical background is included in each chapter, but the primary focus is on using Stata and interpreting results. This handbook complements its two predecessors A Handbook of Statistical Analyses Using S-Plus and A Handbook of Statistical Analyses Using SAS.

Author: Sophia Rabe-Hesketh
Publisher: CRC Press
ISBN: 9781439832356
Category : Mathematics
Languages : en
Pages : 334

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Book Description
The powerful statistical software Stata has streamlined data analysis, interpretation, and presentation for researchers and statisticians around the world. But because of its power and plethora of features, particularly in version 8, Stata manuals are usually quite extensive and detailed. The third edition of the Handbook of Statistical Analyses Using Stata describes the features of Stata version 8 in the same concise, convenient format that made the previous editions so popular. But the revisions updating the handbook to version 8 are not all this edition has to offer: the authors also added important material in three all-new chapters and focused more attention on Stata's improved graphical features. More Highlights of the Third Edition Ö Updates in all chapters that reflect the features of Stata 8 Ö A new chapter on random effects models Ö A new chapter on generalized estimating equations Ö A new chapter on cluster analysis Ö Increased emphasis on diagnostics Each chapter deals with a particular data set, identifies the appropriate analysis for it, and while it includes a brief account of the statistical background of the technique applied, the primary focus remains firmly on using Stata 8 and interpreting its results. Ideal for researchers, statisticians, and students alike, this handbook forms a perfect complement to the Stata manuals, by giving new users a head start on using the program and providing experienced users with a handy quick reference.

Author: Torsten Hothorn
Publisher: CRC Press
ISBN: 1482204584
Category : Mathematics
Languages : en
Pages : 454

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Book Description
Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis. New to the Third Edition Three new chapters on quantile regression, missing values, and Bayesian inference Extra material in the logistic regression chapter that describes a regression model for ordered categorical response variables Additional exercises More detailed explanations of R code New section in each chapter summarizing the results of the analyses Updated version of the HSAUR package (HSAUR3), which includes some slides that can be used in introductory statistics courses Whether you’re a data analyst, scientist, or student, this handbook shows you how to easily use R to effectively evaluate your data. With numerous real-world examples, it emphasizes the practical application and interpretation of results.

Author: Torsten Hothorn
Publisher: Chapman and Hall/CRC
ISBN: 9781420079333
Category : Mathematics
Languages : en
Pages : 376

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Book Description
A Proven Guide for Easily Using R to Effectively Analyze Data Like its bestselling predecessor, A Handbook of Statistical Analyses Using R, Second Edition provides a guide to data analysis using the R system for statistical computing. Each chapter includes a brief account of the relevant statistical background, along with appropriate references. New to the Second Edition New chapters on graphical displays, generalized additive models, and simultaneous inference A new section on generalized linear mixed models that completes the discussion on the analysis of longitudinal data where the response variable does not have a normal distribution New examples and additional exercises in several chapters A new version of the HSAUR package (HSAUR2), which is available from CRAN This edition continues to offer straightforward descriptions of how to conduct a range of statistical analyses using R, from simple inference to recursive partitioning to cluster analysis. Focusing on how to use R and interpret the results, it provides students and researchers in many disciplines with a self-contained means of using R to analyze their data.

Author: Sabine Landau
Publisher: Chapman & Hall/CRC
ISBN: 9781138462496
Category : SPSS (Computer file)
Languages : en
Pages : 0

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Book Description
Shows how to conduct a range of univariate and multivariate statistical analysis using the Statistical Package for the Social Sciences, version 11. This title addresses various types of analytical procedure that are applied to data sets, primarily from the social and behavioral sciences areas. It is suitable for researchers in psychology.

Author: Torsten Hothorn
Publisher: Chapman and Hall/CRC
ISBN: 9781584885399
Category : Mathematics
Languages : en
Pages : 304

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Book Description
R is dynamic, to say the least. More precisely, it is organic, with new functionality and add-on packages appearing constantly. And because of its open-source nature and free availability, R is quickly becoming the software of choice for statistical analysis in a variety of fields. Doing for R what Everitt's other Handbooks have done for S-PLUS, STATA, SPSS, and SAS, A Handbook of Statistical Analyses Using R presents straightforward, self-contained descriptions of how to perform a variety of statistical analyses in the R environment. From simple inference to recursive partitioning and cluster analysis, eminent experts Everitt and Hothorn lead you methodically through the steps, commands, and interpretation of the results, addressing theory and statistical background only when useful or necessary. They begin with an introduction to R, discussing the syntax, general operators, and basic data manipulation while summarizing the most important features. Numerous figures highlight R's strong graphical capabilities and exercises at the end of each chapter reinforce the techniques and concepts presented. All data sets and code used in the book are available as a downloadable package from CRAN, the R online archive. A Handbook of Statistical Analyses Using R is the perfect guide for newcomers as well as seasoned users of R who want concrete, step-by-step guidance on how to use the software easily and effectively for nearly any statistical analysis.

Author: Michael N Mitchell
Publisher: Stata Press
ISBN: 9781597183185
Category :
Languages : en
Pages : 512

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Book Description
This second edition of Data Management Using Stata focuses on tasks that bridge the gap between raw data and statistical analysis. It has been updated throughout to reflect new data management features that have been added over the last 10 years. Such features include the ability to read and write a wide variety of file formats, the ability to write highly customized Excel files, the ability to have multiple Stata datasets open at once, and the ability to store and manipulate string variables stored as Unicode. Further, this new edition includes a new chapter illustrating how to write Stata programs for solving data management tasks. As in the original edition, the chapters are organized by data management areas: reading and writing datasets, cleaning data, labeling datasets, creating variables, combining datasets, processing observations across subgroups, changing the shape of datasets, and programming for data management. Within each chapter, each section is a self-contained lesson illustrating a particular data management task (for instance, creating date variables or automating error checking) via examples. This modular design allows you to quickly identify and implement the most common data management tasks without having to read background information first. In addition to the "nuts and bolts" examples, author Michael Mitchell alerts users to common pitfalls (and how to avoid them) and provides strategic data management advice. This book can be used as a quick reference for solving problems as they arise or can be read as a means for learning comprehensive data management skills. New users will appreciate this book as a valuable way to learn data management, while experienced users will find this information to be handy and time saving--there is a good chance that even the experienced user will learn some new tricks.

Author: Kyle C. Longest
Publisher: SAGE Publications
ISBN: 1483356647
Category : Social Science
Languages : en
Pages : 282

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Book Description
Using Stata for Quantitative Analysis, Second Edition offers a brief, but thorough introduction to analyzing data with Stata software. It can be used as a reference for any statistics or methods course across the social, behavioral, and health sciences since these fields share a relatively similar approach to quantitative analysis. In this book, author Kyle Longest teaches the language of Stata from an intuitive perspective, furthering students’ overall retention and allowing a student with no experience in statistical software to work with data in a very short amount of time. The self-teaching style of this book enables novice Stata users to complete a basic quantitative research project from start to finish. The Second Edition covers the use of Stata 13 and can be used on its own or as a supplement to a research methods or statistics textbook.

Author: Christopher F. Baum
Publisher: Stata Press
ISBN: 1597180130
Category : Business & Economics
Languages : en
Pages : 362

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Book Description
Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, this introduction illustrates how to apply econometric theories used in modern empirical research using Stata. The author emphasizes the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how to apply the theories to real data sets. The book first builds familiarity with the basic skills needed to work with econometric data in Stata before delving into the core topics, which range from the multiple linear regression model to instrumental-variables estimation.