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Author: Alan Agresti
Publisher: John Wiley & Sons
ISBN: 1119405270
Category : Mathematics
Languages : en
Pages : 400
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Book Description
A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis • New sections in many chapters introducing the Bayesian approach for the methods of that chapter • More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets • An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.
Author: Alan Agresti
Publisher: John Wiley & Sons
ISBN: 1119405270
Category : Mathematics
Languages : en
Pages : 400
Get Book Here
Book Description
A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis • New sections in many chapters introducing the Bayesian approach for the methods of that chapter • More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets • An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.
Author: Leo A. Goodman
Publisher:
ISBN:
Category :
Languages : sl
Pages :
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Book Description
Author: Leo A. Goodman
Publisher: University Press of America
ISBN:
Category : Mathematics
Languages : en
Pages : 498
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Book Description
Abstract: Statistical methods covering log-linear models and latent-structure analysis are presented and described for the analysis of qualitative or categorical data to assist the pressing needs of social researchers and others in developing and applying a unified and systematic approach to the analysis of such data. The scope of applications in this approach includes methods for the sociologist examining the relationship between poverty and crime; the educational researcher examining the reliability and validity of a set of test items; the psychometrician developing a new measurement scale; the market researcher analyzing purchase behavior in different market segments; the medical researcher attempting to identify factors associated with various diseases (e.g., breast cancer); and the political scientist examining voter behavior. The methods are applicable to computer programs. (wz).
Author: Graham R Gibbs
Publisher: SAGE Publications Limited
ISBN: 9781473915817
Category : Social Science
Languages : en
Pages : 232
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Book Description
This book tackles the challenges of how to make sense of qualitative data. It offers students and researchers a hands-on guide to the practicalities of coding, comparing data, and using computer-assisted qualitative data analysis. Lastly, Gibbs shows you how to bring it all together, so you can see the steps of qualitative analysis, understand the central place of coding, ensure analytic quality and write effectively to present your results.
Author: Ian Dey
Publisher: Routledge
ISBN: 1134931468
Category : Psychology
Languages : en
Pages : 309
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Book Description
Qualitative Data Analysis shows that learning how to analyse qualitative data by computer can be fun. Written in a stimulating style, with examples drawn mainly from every day life and contemporary humour, it should appeal to a wide audience.
Author: Daniel Navarro
Publisher: Lulu.com
ISBN: 1326189727
Category : Computers
Languages : en
Pages : 617
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Book Description
"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
Author: Udo Kuckartz
Publisher: Springer
ISBN: 3030156710
Category : Social Science
Languages : en
Pages : 293
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Book Description
This book presents strategies for analyzing qualitative and mixed methods data with MAXQDA software, and provides guidance on implementing a variety of research methods and approaches, e.g. grounded theory, discourse analysis and qualitative content analysis, using the software. In addition, it explains specific topics, such as transcription, building a coding frame, visualization, analysis of videos, concept maps, group comparisons and the creation of literature reviews. The book is intended for masters and PhD students as well as researchers and practitioners dealing with qualitative data in various disciplines, including the educational and social sciences, psychology, public health, business or economics.
Author: Melissa Freeman
Publisher: Routledge
ISBN: 1315516837
Category : Education
Languages : en
Pages : 234
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Book Description
Modes of Thinking for Qualitative Data Analysis argues for engagement with the conceptual underpinnings of five prominent analytical strategies used by qualitative researchers: Categorical Thinking, Narrative Thinking, Dialectical Thinking, Poetical Thinking, and Diagrammatical Thinking. By presenting such disparate modes of research in the space of a single text, Freeman not only draws attention to the distinct methodological and theoretical contributions of each, she also establishes a platform for choosing among particular research strategies by virtue of their strengths and limitations. Experienced qualitative researchers, novices, and graduate students from many disciplines will gain new insight from the theory-practice relationship of analysis advanced in this text.
Author: Udo Kuckartz
Publisher: SAGE
ISBN: 1446297764
Category : Reference
Languages : en
Pages : 193
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Book Description
How can you analyse narratives, interviews, field notes, or focus group data? Qualitative text analysis is ideal for these types of data and this textbook provides a hands-on introduction to the method and its theoretical underpinnings. It offers step-by-step instructions for implementing the three principal types of qualitative text analysis: thematic, evaluative, and type-building. Special attention is paid to how to present your results and use qualitative data analysis software packages, which are highly recommended for use in combination with qualitative text analysis since they allow for fast, reliable, and more accurate analysis. The book shows in detail how to use software, from transcribing the verbal data to presenting and visualizing the results. The book is intended for Master’s and Doctoral students across the social sciences and for all researchers concerned with the systematic analysis of texts of any kind.
Author: Erling B. Andersen
Publisher: Springer Science & Business Media
ISBN: 3642973531
Category : Business & Economics
Languages : en
Pages : 542
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Book Description
The aim of this book is to give an up to date account of the most commonly uses statisti cal models for categorical data. The emphasis is on the connection between theory and applications to real data sets. The book only covers models for categorical data. Various models for mixed continuous and categorical data are thus excluded. The book is written as a textbook, although many methods and results are quite recent. This should imply, that the book can be used for a graduate course in categorical data analysis. With this aim in mind chapters 3 to 12 are concluded with a set of exer cises. 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. A certain amount of general knowledge of statistical theory is necessary to fully benefit from the book. A summary of the basic statistical concepts deemed necessary pre requisites is given in chapter 2. The mathematical level is only moderately high, but the account iu chapter 3 of basic properties of exponential families aud the parametric llluitillOl1lia.l distribuLioll is made as mathematical precise as possible without going into mathematical details and leaving out most proofs.
