Автор: Liu, Xing Название: Categorical data analysis and multilevel modeling using r ISBN: 1544324901 ISBN-13(EAN): 9781544324906 Издательство: Sage Publications Рейтинг: Цена: 18058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Categorical Data Analysis and Multilevel Modeling Using Rprovides a practical guide to regression techniques for analyzing binary, ordinal, nominal, and count response variables using the R software. Author Xing Liu offers a unified framework for both single-level and multilevel modeling of categorical and count response variables with both frequentist and Bayesian approaches. Each chapter demonstrates how to conduct the analysis using R, how to interpret the models, and how to present the results for publication. A companion website for this book contains datasets and R commands used in the book for students, and solutions for the end-of-chapter exercises on the instructor site.
Автор: Guogen Shan Название: Exact Statistical Inference for Categorical Data ISBN: 0081006810 ISBN-13(EAN): 9780081006818 Издательство: Elsevier Science Рейтинг: Цена: 8757.00 р. Наличие на складе: Поставка под заказ.
Описание:
Exact Statistical Inference for Categorical Data discusses the way asymptotic approaches have been often used in practice to make statistical inference. This book introduces both conditional and unconditional exact approaches for the data in 2 by 2, or 2 by k contingency tables, and is an ideal reference for users who are interested in having the convenience of applying asymptotic approaches, with less computational time. In addition to the existing conditional exact inference, some efficient, unconditional exact approaches could be used in data analysis to improve the performance of the testing procedure.
Demonstrates how exact inference can be used to analyze data in 2 by 2 tables
Discusses the analysis of data in 2 by k tables using exact inference
Explains how exact inference can be used in genetics
Автор: Xu, Jun Название: Modern applied regressions ISBN: 0367173875 ISBN-13(EAN): 9780367173876 Издательство: Taylor&Francis Рейтинг: Цена: 13779.00 р. Наличие на складе: Поставка под заказ.
Описание: Modern Applied Regressions creates an intricate mural with mosaics of categorical and limited response variable (CLRV) models using both Bayesian and Frequentist approaches. Written for graduate students, junior researchers, and quantitative analysts in behavioral, health, and social sciences.
Описание: Social science and behavioral science students and researchers are often confronted with data that are categorical, count a phenomenon, or have been collected over time. This book provides an introduction and overview of several statistical models designed for these types of outcomes.
Автор: Wicher Bergsma; Marcel A. Croon; Jacques A. Hagena Название: Marginal Models ISBN: 1441918736 ISBN-13(EAN): 9781441918734 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Marginal models are often the best way of answering research questions involving dependent observations. This comprehensive overview of the basic principles of marginal modeling offers a wide range of possible applications through many real world examples.
Автор: Helge Toutenburg Название: Experimental Design and Model Choice ISBN: 3642525008 ISBN-13(EAN): 9783642525001 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Powers, Daniel Xie, Yu Название: Statistical methods for categorical data analysis ISBN: 0123725623 ISBN-13(EAN): 9780123725622 Издательство: Emerald Рейтинг: Цена: 11585.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social science research. Companion website also available, at https://webspace.utexas.edu/dpowers/www/
Автор: Roverato Alberto Название: Graphical Models for Categorical Data ISBN: 1108404960 ISBN-13(EAN): 9781108404969 Издательство: Cambridge Academ Рейтинг: Цена: 4750.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: For advanced students of network data science, this compact account covers both well-established methodology and the theory of models recently introduced in the graphical model literature. It focuses on the discrete case where all variables involved are categorical and, in this context, it achieves a unified presentation of classical and recent results.
Автор: Erling B. Andersen Название: The Statistical Analysis of Categorical Data ISBN: 364278819X ISBN-13(EAN): 9783642788192 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The aim of this book is to give an up to date account of the most commonly uses statisti- cal models for categorical data. In many cases, the data sets are those data sets, which were not included in the examples of the book, although they at one point in time were regarded as potential can- didates for an example.
Автор: Jeffrey S. Simonoff Название: Analyzing Categorical Data ISBN: 144191837X ISBN-13(EAN): 9781441918376 Издательство: Springer Рейтинг: Цена: 12850.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Categorical data arise often in many fields, including biometrics, economics, management, manufacturing, marketing, psychology, and sociology. This book provides an introduction to the analysis of such data. The coverage is broad, using the loglinear Poisson regression model and logistic binomial regression models as the primary engines for methodology. Topics covered include count regression models, such as Poisson, negative binomial, zero-inflated, and zero-truncated models; loglinear models for two-dimensional and multidimensional contingency tables, including for square tables and tables with ordered categories; and regression models for two-category (binary) and multiple-category target variables, such as logistic and proportional odds models.
All methods are illustrated with analyses of real data examples, many from recent subject area journal articles. These analyses are highlighted in the text, and are more detailed than is typical, providing discussion of the context and background of the problem, model checking, and scientific implications. More than 200 exercises are provided, many also based on recent subject area literature. Data sets and computer code are available at a web site devoted to the text. Adopters of this book may request a solutions manual from: textbook@springer-ny.com.
From the reviews:
"Jeff Simonoff's book is at the top of the heap of categorical data analysis textbooks...The examples are superb. Student reactions in a class I taught from this text were uniformly positive, particularly because of the examples and exercises. Additional materials related to the book, particularly code for S-Plus, SAS, and R, useful for analysis of examples, can be found at the author's Web site at New York University. I liked this book for this reason, and recommend it to you for pedagogical purposes." (Stanley Wasserman, The American Statistician, August 2006, Vol. 60, No. 3)
"The book has various noteworthy features. The examples used are from a variety of topics, including medicine, economics, sports, mining, weather, as well as social aspects like needle-exchange programs. The examples motivate the theory and also illustrate nuances of data analytical procedures. The book also incorporates several newer methods for analyzing categorical data, including zero-inflated Poisson models, robust analysis of binomial and poisson models, sandwich estimators, multinomial smoothing, ordinal agreement tables...this is definitely a good reference book for any researcher working with categorical data." Technometrics, May 2004
"This guide provides a practical approach to the appropriate analysis of categorical data and would be a suitable purchase for individuals with varying levels of statistical understanding." Paediatric and Perinatal Epidemiology, 2004, 18
"This book gives a fresh approach to the topic of categorical data analysis. The presentation of the statistical methods exploits the connection to regression modeling with a focus on practical features rather than formal theory...There is much to learn from this book. Aside from the ordinary materials such as association diagrams, Mantel-Haenszel estimators, or overdispersion, the reader will also find some less-often presented but interesting and stimulating topics... T]his is an excellent book, giving an up-to-date introduction to the wide field of analyzing categorical data." Biometrics, September 2004
..".It is of great help to data
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