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Bayesian Analysis with Stata, Thompson John

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Цена: 5851р.
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Автор: Thompson John
Название:  Bayesian Analysis with Stata   (Джон Томпсон: Байесовский анализ с помощью Stata)
Издательство: Taylor&Francis
Классификация:
Вероятность и статистика

ISBN: 1597181412
ISBN-13(EAN): 9781597181419
ISBN: 1-59718-141-2
ISBN-13(EAN): 978-1-59718-141-9
Обложка/Формат: Paperback
Страницы: 302
Вес: 0.62 кг.
Дата издания: 12.06.2014
Серия: Mathematics
Язык: ENG
Иллюстрации: Illustrations
Размер: 22.61 x 18.29 x 2.03 cm
Читательская аудитория: Tertiary education (us: college)
Ключевые слова: Probability & statistics, MATHEMATICS / Probability & Statistics / General,MATHEMATICS / Probability & Statistics / Bayesian Analysis
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Поставляется из: Англии
Описание:

Bayesian Analysis with Stata is written for anyone interested in applying Bayesian methods to real data easily. The book shows how modern analyses based on Markov chain Monte Carlo (MCMC) methods are implemented in Stata both directly and by passing Stata datasets to OpenBUGS or WinBUGS for computation, allowing Statas data management and graphing capability to be used with OpenBUGS/WinBUGS speed and reliability.

The book emphasizes practical data analysis from the Bayesian perspective, and hence covers the selection of realistic priors, computational efficiency and speed, the assessment of convergence, the evaluation of models, and the presentation of the results. Every topic is illustrated in detail using real-life examples, mostly drawn from medical research.

The book takes great care in introducing concepts and coding tools incrementally so that there are no steep patches or discontinuities in the learning curve. The books content helps the user see exactly what computations are done for simple standard models and shows the user how those computations are implemented. Understanding these concepts is important for users because Bayesian analysis lends itself to custom or very complex models, and users must be able to code these themselves.





Meta-Analysis in Stata

Автор: Tom M. Palmer and Jonathan A. C. Sterne (editors)
Название: Meta-Analysis in Stata
ISBN: 1597181471 ISBN-13(EAN): 9781597181471
Издательство: Taylor&Francis
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Цена: 7941 р.
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Описание: Meta-analysis allows researchers to combine the results of several studies into a unified analysis that provides an overall estimate of the effect of interest. This collection of articles from the Stata Journal and Stata Technical Bulletin will be indispensable to researchers who wish to conduct meta-analyses using Stata and learn about the full range of user-written Stata meta-analysis commands. With these articles and the associated Stata software, you gain access to the statistical methods behind the rapid increase in the number of meta-analyses reported in the social and medical literature. Collectively, the articles provide a detailed description of a range of meta-analytic methods. They show how to conduct and interpret meta-analyses; how to produce highly flexible graphical displays; how to use meta-regression; how to examine bias; how to conduct individual participant data meta-analysis; and how to conduct multivariate meta-analysis. This edition also contains three articles on network metaanalysis, a major recent development in meta-analysis methodology.

Regression Models for Categorical Dependent Variables Using Stata, Third Edition

Автор: Long
Название: Regression Models for Categorical Dependent Variables Using Stata, Third Edition
ISBN: 1597181110 ISBN-13(EAN): 9781597181112
Издательство: Taylor&Francis
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Цена: 8777 р.
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Описание: Regression Models for Categorical Dependent Variables Using Stata, Third Edition shows how to use Stata to fit and interpret regression models for categorical data. The third edition is a complete rewrite of the book. Factor variables and the margins command changed how the effects of variables can be estimated and interpreted. In addition, the authors' views on interpretation have evolved. The changes to Stata and to the authors' views inspired the authors to completely rewrite their popular SPost commands to take advantage of the power of the margins command and the flexibility of factor-variable notation. The new edition will interest readers of a previous edition as well as new readers. Even though about 150 pages of appendixes were removed, the third edition is about 60 pages longer than the second. Although regression models for categorical dependent variables are common, few texts explain how to interpret such models; this text fills the void. With the book, Long and Freese provide a suite of commands for model interpretation, hypothesis testing, and model diagnostics. The new commands that accompany the third edition make it easy to include powers or interactions of covariates in regression models and work seamlessly with models estimated with complex survey data. The authors' new commands greatly simplify the use of margins, in the same way that the marginsplot command harnesses the power of margins for plotting predictions. The authors discuss how to use margins and their new mchange, mtable, and mgen commands to compute tables and to plot predictions. They also discuss how to use these commands to estimate marginal effects, averaged either over the sample or at fixed values of the regressors. The authors introduce and advocate a variety of new methods that use predictions to interpret the effect of variables in regression models. The third edition begins with an excellent introduction to Stata and follows with general treatments of the estimation, testing, fit, and interpretation of this class of models. New to the third edition is an entire chapter about how to interpret regression models using predictions—a chapter that is expanded upon in later chapters that focus on models for binary, ordinal, nominal, and count outcomes. Long and Freese use many concrete examples in their third edition. All the examples, datasets, and author-written commands are available on the authors' website, so readers can easily replicate the examples with Stata. This book is ideal for students or applied researchers who want to learn how to fit and interpret models for categorical data.

Applied Statistics Using Stata

Автор: Mehmet Mehmetoglu and Tor Georg Jakobsen
Название: Applied Statistics Using Stata
ISBN: 1473913233 ISBN-13(EAN): 9781473913233
Издательство: Sage Publications
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Цена: 3945 р.
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Описание: Clear, intuitive and written with the social science student in mind, this book represents the ideal combination of statistical theory and practice. It focuses on questions that can be answered using statistics and addresses common themes and problems in a straightforward, easy-to-follow manner. The book carefully combines the conceptual aspects of statistics with detailed technical advice providing both the ‘why’ of statistics and the ‘how’. Built upon a variety of engaging examples from across the social sciences it provides a rich collection of statistical methods and models. Students are encouraged to see the impact of theory whilst simultaneously learning how to manipulate software to meet their needs. The book also provides: Original case studies and data sets Practical guidance on how to run and test models in Stata Downloadable Stata programmes created to work alongside chapters A wide range of detailed applications using Stata Step-by-step notes on writing the relevant code. This excellent text will give anyone doing statistical research in the social sciences the theoretical, technical and applied knowledge needed to succeed.

An Introduction to Multivariate Statistical Analysis, Third Edition

Автор: T. W. Anderson
Название: An Introduction to Multivariate Statistical Analysis, Third Edition
ISBN: 0471360910 ISBN-13(EAN): 9780471360919
Издательство: Wiley
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Цена: 16302 р.
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Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.

Data Analysis Using Stata, Third Edition

Автор: Kohler
Название: Data Analysis Using Stata, Third Edition
ISBN: 1597181102 ISBN-13(EAN): 9781597181105
Издательство: Taylor&Francis
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Цена: 7627 р.
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Описание: Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. Readers already familiar with Stata will find it an enjoyable resource for picking up new tips and tricks. The book is written as a self-study tutorial and organized around examples. It interactively introduces statistical techniques such as data exploration, description, and regression techniques for continuous and binary dependent variables. Step by step, readers move through the entire process of data analysis and in doing so learn the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition includes advanced topics, such as factor-variables notation, average marginal effects, standard errors in complex survey, and multiple imputation in a way, that beginners of both data analysis and Stata can understand. Using data from a longitudinal study of private households, the authors provide examples from the social sciences that are relatable to researchers from all disciplines. The examples emphasize good statistical practice and reproducible research. Readers are encouraged to download the companion package of datasets to replicate the examples as they work through the book. Each chapter ends with exercises to consolidate acquired skills.

An Introduction to Stata Programming

Автор: Baum, Christopher F.|
Название: An Introduction to Stata Programming
ISBN: 1597180459 ISBN-13(EAN): 9781597180450
Издательство: Taylor&Francis
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Цена: 4701 р.
Наличие на складе: Поставка под заказ.

Описание:

This work focuses on three types of Stata programming: do-file programming, ado-file programming, and Mata functions that work in conjunction with do- and ado-files. It explains how to usefully automate work with Stata and how to use Stata more effectively through programming on one or more of these levels. After presenting elementary concepts of the command-line interface and commonly used tools for working with programs and data sets, the text follows a unique format by offering "cookbook" chapters after each main chapter. These cookbook chapters look at how to perform a specific programming task with Stata and provide a complete solution to the problem. The text also includes numerous examples of Mata, Stata's matrix programming language.

Handbook of Statistical Analyses Using Stata, Fourth Edition

Автор: Everitt
Название: Handbook of Statistical Analyses Using Stata, Fourth Edition
ISBN: 1584887567 ISBN-13(EAN): 9781584887560
Издательство: Taylor&Francis
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Цена: 5746 р.
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Описание: Fully updated, the fourth edition of this highly acclaimed and perpetually bestselling text demonstrates how a wide variety of statistical analyses, including descriptive statistics, graphics, and model estimation and diagnostics, can be performed using Stata version 9. The authors present many of Stata’s novel features, including a new mixed-models estimation command and a new matrix language. This edition also contains additional exercises that use various data sets and numerous examples of real-life data, enabling a better understanding of the methodology. The book offers selected solutions in an appendix as well as a solutions manual with qualifying course adoptions.

An Introduction to Forecasting Time Series Using Stata

Автор: Yaffee, Robert|
Название: An Introduction to Forecasting Time Series Using Stata
ISBN: 1597180157 ISBN-13(EAN): 9781597180153
Издательство: Taylor&Francis
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Цена: 5642 р.
Наличие на складе: Поставка под заказ.

Описание: Explores forecasting times series with Stata 10. This work presents theory, modeling, programming, and interpretation of the major time series models, along with interesting applications to business and risk analysis in finance. It shows how to apply these techniques to real-life social science, economic, business, financial and medical data.

Multilevel and Longitudinal Modeling Using Stata, Second Edition

Автор: Rabe-Hesketh, Sophia | Skrondal, Anders|
Название: Multilevel and Longitudinal Modeling Using Stata, Second Edition
ISBN: 1597180408 ISBN-13(EAN): 9781597180405
Издательство: Taylor&Francis
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Цена: 6269 р.
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Data Management Using Stata

Автор: Mitchell
Название: Data Management Using Stata
ISBN: 1597180769 ISBN-13(EAN): 9781597180764
Издательство: Taylor&Francis
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Цена: 5015 р.
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Описание: Using simple language and illustrative examples, this book comprehensively covers data management tasks that bridge the gap between raw data and statistical analysis. Rather than focus on clusters of commands, the author takes a modular approach that enables readers to quickly identify and implement the necessary task without having to access background information first. Each section presents a self-contained lesson that uses examples to illustrate a particular data management task, such as creating data variables and automating error-checking. The text also discusses common pitfalls and how to avoid them, providing strategic data management advice.

Discovering Structural Equation Modeling Using Stata

Автор: Acock
Название: Discovering Structural Equation Modeling Using Stata
ISBN: 1597181390 ISBN-13(EAN): 9781597181396
Издательство: Taylor&Francis
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Цена: 7941 р.
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Описание: Discovering Structural Equation Modeling Using Stata, Revised Edition is devoted to Stata’s sem command and all it can do. Learn about its capabilities in the context of confirmatory factor analysis, path analysis, structural equation modeling, longitudinal models, and multiple-group analysis. Each model is presented along with the necessary Stata code, which is parsimonious, powerful, and can be modified to fit a wide variety of models. The datasets used are downloadable, offering a hands-on approach to learning. A particularly exciting feature of Stata is the SEM Builder. This graphical interface for structural equation modeling allows you to draw publication-quality path diagrams and fit the models without writing any programming code. When you fit a model with the SEM Builder, Stata automatically generates the complete code that you can save for future use. Use of this unique tool is extensively covered in an appendix and brief examples appear throughout the text.

An Introduction to Stata for Health Researchers, Fourth Edition

Автор: Svend Juul, Morten Frydenberg
Название: An Introduction to Stata for Health Researchers, Fourth Edition
ISBN: 1597181358 ISBN-13(EAN): 9781597181358
Издательство: Taylor&Francis
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Цена: 7941 р.
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Описание: An Introduction to Stata for Health Researchers, Fourth Edition methodically covers data management, simple description and analysis, and more advanced analyses often used in health research, including regression models, survival analysis, and evaluation of diagnostic methods. A chapter on graphics explores most graph types and describes how to modify the appearance of a graph before submitting it for publication. The authors emphasize the importance of good documentation habits to prevent errors and wasted time. Demonstrating the use of strategies and tools for documentation, they provide robust examples and offer the datasets for download online. Updated to correspond to Stata 13, this fourth edition is written for both Windows and Mac users. It provides improved online documentation, including further reading in online manuals.


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