Bayesian Models For Categorical Data


Bayesian Models For Categorical Data
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Bayesian Models For Categorical Data


Bayesian Models For Categorical Data
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Author : Peter Congdon
language : en
Publisher: John Wiley & Sons
Release Date : 2005-12-13

Bayesian Models For Categorical Data written by Peter Congdon 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 2005-12-13 with Mathematics categories.


The use of Bayesian methods for the analysis of data has grown substantially in areas as diverse as applied statistics, psychology, economics and medical science. Bayesian Methods for Categorical Data sets out to demystify modern Bayesian methods, making them accessible to students and researchers alike. Emphasizing the use of statistical computing and applied data analysis, this book provides a comprehensive introduction to Bayesian methods of categorical outcomes. * Reviews recent Bayesian methodology for categorical outcomes (binary, count and multinomial data). * Considers missing data models techniques and non-standard models (ZIP and negative binomial). * Evaluates time series and spatio-temporal models for discrete data. * Features discussion of univariate and multivariate techniques. * Provides a set of downloadable worked examples with documented WinBUGS code, available from an ftp site. The author's previous 2 bestselling titles provided a comprehensive introduction to the theory and application of Bayesian models. Bayesian Models for Categorical Data continues to build upon this foundation by developing their application to categorical, or discrete data - one of the most common types of data available. The author's clear and logical approach makes the book accessible to a wide range of students and practitioners, including those dealing with categorical data in medicine, sociology, psychology and epidemiology.



Computational Issues In The Bayesian Analysis Of Categorical Data


Computational Issues In The Bayesian Analysis Of Categorical Data
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Author : Michael J. Evans
language : en
Publisher:
Release Date : 1990

Computational Issues In The Bayesian Analysis Of Categorical Data written by Michael J. Evans and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Bayesian statistical decision theory categories.




Statistical Methods For Categorical Data Analysis


Statistical Methods For Categorical Data Analysis
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Author : Daniel Powers
language : en
Publisher: Emerald Group Publishing
Release Date : 2008-11-13

Statistical Methods For Categorical Data Analysis written by Daniel Powers and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-13 with Psychology categories.


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/



A Course In Categorical Data Analysis


A Course In Categorical Data Analysis
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Author : Thomas Leonard
language : en
Publisher: CRC Press
Release Date : 2020-08-26

A Course In Categorical Data Analysis written by Thomas Leonard and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-26 with Mathematics categories.


Categorical data-comprising counts of individuals, objects, or entities in different categories-emerge frequently from many areas of study, including medicine, sociology, geology, and education. They provide important statistical information that can lead to real-life conclusions and the discovery of fresh knowledge. Therefore, the ability to manipulate, understand, and interpret categorical data becomes of interest-if not essential-to professionals and students in a broad range of disciplines. Although t-tests, linear regression, and analysis of variance are useful, valid methods for analysis of measurement data, categorical data requires a different methodology and techniques typically not encountered in introductory statistics courses. Developed from long experience in teaching categorical analysis to a multidisciplinary mix of undergraduate and graduate students, A Course in Categorical Data Analysis presents the easiest, most straightforward ways of extracting real-life conclusions from contingency tables. The author uses a Fisherian approach to categorical data analysis and incorporates numerous examples and real data sets. Although he offers S-PLUS routines through the Internet, readers do not need full knowledge of a statistical software package. In this unique text, the author chooses methods and an approach that nurtures intuitive thinking. He trains his readers to focus not on finding a model that fits the data, but on using different models that may lead to meaningful conclusions. The book offers some simple, innovative techniques not highighted in other texts that help make the book accessible to a broad, interdisciplinary audience. A Course in Categorical Data Analysis enables readers to quickly use its offering of tools for drawing scientific, medical, or real-life conclusions from categorical data sets.



Trends And Challenges In Categorical Data Analysis


Trends And Challenges In Categorical Data Analysis
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Author : Maria Kateri
language : en
Publisher: Springer Nature
Release Date : 2023-07-08

Trends And Challenges In Categorical Data Analysis written by Maria Kateri and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-08 with Mathematics categories.


This book provides a selection of modern and sophisticated methodologies for the analysis of large and complex univariate and multivariate categorical data. It gives an overview of a substantive and broad collection of topics in the analysis of categorical data, including association, marginal and graphical models, time series and fixed effects models, as well as modern methods of estimation such as regularization, Bayesian estimation and bias reduction methods, along with new simple measures for model interpretability. Methodological innovations and developments are illustrated and explained through real-world applications, together with useful R packages, allowing readers to replicate most of the analyses using the provided code. The applications span a variety of disciplines, including education, psychology, health, economics, and social sciences.



Categorical Data Analysis And Multilevel Modeling Using R


Categorical Data Analysis And Multilevel Modeling Using R
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Author : Xing Liu
language : en
Publisher: SAGE Publications
Release Date : 2022-02-25

Categorical Data Analysis And Multilevel Modeling Using R written by Xing Liu and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-25 with Social Science categories.


Categorical Data Analysis and Multilevel Modeling Using R provides 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.



Modern Applied Regressions


Modern Applied Regressions
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Author : Jun Xu
language : en
Publisher: CRC Press
Release Date : 2022-12-08

Modern Applied Regressions written by Jun Xu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-08 with Mathematics categories.


Modern Applied Regressions creates an intricate and colorful 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, this text provides details for doing Bayesian and frequentist data analysis of CLRV models. Each chapter can be read and studied separately with R coding snippets and template interpretation for easy replication. Along with the doing part, the text provides basic and accessible statistical theories behind these models and uses a narrative style to recount their origins and evolution. This book first scaffolds both Bayesian and frequentist paradigms for regression analysis, and then moves onto different types of categorical and limited response variable models, including binary, ordered, multinomial, count, and survival regression. Each of the middle four chapters discusses a major type of CLRV regression that subsumes an array of important variants and extensions. The discussion of all major types usually begins with the history and evolution of the prototypical model, followed by the formulation of basic statistical properties and an elaboration on the doing part of the model and its extension. The doing part typically includes R codes, results, and their interpretation. The last chapter discusses advanced modeling and predictive techniques—multilevel modeling, causal inference and propensity score analysis, and machine learning—that are largely built with the toolkits designed for the CLRV models previously covered. The online resources for this book, including R and Stan codes and supplementary notes, can be accessed at https://sites.google.com/site/socjunxu/home/statistics/modern-applied-regressions.



Categorical Data Analysis


Categorical Data Analysis
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Author : Alan Agresti
language : en
Publisher: John Wiley & Sons
Release Date : 2013-04-08

Categorical Data Analysis written by Alan Agresti 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 2013-04-08 with Mathematics categories.


Praise for the Second Edition "A must-have book for anyone expecting to do research and/orapplications in categorical data analysis." —Statistics in Medicine "It is a total delight reading this book." —Pharmaceutical Research "If you do any analysis of categorical data, this is anessential desktop reference." —Technometrics The use of statistical methods for analyzing categorical datahas increased dramatically, particularly in the biomedical, socialsciences, and financial industries. Responding to new developments,this book offers a comprehensive treatment of the most importantmethods for categorical data analysis. Categorical Data Analysis, Third Edition summarizes thelatest methods for univariate and correlated multivariatecategorical responses. Readers will find a unified generalizedlinear models approach that connects logistic regression andPoisson and negative binomial loglinear models for discrete datawith normal regression for continuous data. This edition alsofeatures: An emphasis on logistic and probit regression methods forbinary, ordinal, and nominal responses for independent observationsand for clustered data with marginal models and random effectsmodels Two new chapters on alternative methods for binary responsedata, including smoothing and regularization methods,classification methods such as linear discriminant analysis andclassification trees, and cluster analysis New sections introducing the Bayesian approach for methods inthat chapter More than 100 analyses of data sets and over 600 exercises Notes at the end of each chapter that provide references torecent research and topics not covered in the text, linked to abibliography of more than 1,200 sources A supplementary website showing how to use R and SAS; for allexamples in the text, with information also about SPSS and Stataand with exercise solutions Categorical Data Analysis, Third Edition is an invaluabletool for statisticians and methodologists, such as biostatisticiansand researchers in the social and behavioral sciences, medicine andpublic health, marketing, education, finance, biological andagricultural sciences, and industrial quality control.



New Developments In Categorical Data Analysis For The Social And Behavioral Sciences


New Developments In Categorical Data Analysis For The Social And Behavioral Sciences
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Author : L. Andries van der Ark
language : en
Publisher: Psychology Press
Release Date : 2005-01-15

New Developments In Categorical Data Analysis For The Social And Behavioral Sciences written by L. Andries van der Ark and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-15 with Business & Economics categories.


Categorical data are quantified as either nominal variables--distinguishing different groups, for example, based on socio-economic status, education, and political persuasion--or ordinal variables--distinguishing levels of interest, such as the preferred politician or the preferred type of punishment for committing burglary. This new book is a collection of up-to-date studies on modern categorical data analysis methods, emphasizing their application to relevant and interesting data sets. This volume concentrates on latent class analysis and item response theory. These methods use latent variables to explain the relationships among observed categorical variables. Latent class analysis yields the classification of a group of respondents according to their pattern of scores on the categorical variables. This provides insight into the mechanisms producing the data and allows the estimation of factor structures and regression models conditional on the latent class structure. Item response theory leads to the identification of one or more ordinal or interval scales. In psychological and educational testing these scales are used for individual measurement of abilities and personality traits. The focus of this volume is applied. After a method is explained, the potential of the method for analyzing categorical data is illustrated by means of a real data example to show how it can be used effectively for solving a real data problem. These methods are accessible to researchers not trained explicitly in applied statistics. This volume appeals to researchers and advanced students in the social and behavioral sciences, including social, developmental, organizational, clinical and health psychologists, sociologists, educational and marketing researchers, and political scientists. In addition, it is of interest to those who collect data on categorical variables and are faced with the problem of how to analyze such variables--among themselves or in relation to metric variables.



Graphical Tools For The Exploration Of Multivariate Categorical Data


Graphical Tools For The Exploration Of Multivariate Categorical Data
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Author : Heike Hofmann
language : en
Publisher: BoD – Books on Demand
Release Date : 2001

Graphical Tools For The Exploration Of Multivariate Categorical Data written by Heike Hofmann and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Multivariate analysis categories.