Bayesian Estimation Methods For Categorical Data

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Categorical Data Analysis

Alan Agresti
Categorical Data Analysis Book PDF

Author : Alan Agresti
Publisher : John Wiley & Sons
Page : 734 pages
File Size : 52,6 Mb
Release : 2003-03-31
Category : Mathematics
ISBN : 9780471458760

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Categorical Data Analysis by Alan Agresti Pdf

Amstat News asked three review editors to rate their topfive favorite books in the September 2003 issue. CategoricalData Analysis was among those chosen. A valuable new edition of a standard reference "A 'must-have' book for anyone expecting to do research and/orapplications in categorical data analysis." –Statistics in Medicine on Categorical Data Analysis,First Edition The use of statistical methods for categorical data hasincreased dramatically, particularly for applications in thebiomedical and social sciences. Responding to new developments inthe field as well as to the needs of a new generation ofprofessionals and students, this new edition of the classicCategorical Data Analysis offers a comprehensiveintroduction to the most important methods for categorical dataanalysis. Designed for statisticians and biostatisticians as well asscientists and graduate students practicing statistics,Categorical Data Analysis, Second 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 regression for discrete data withnormal regression for continuous data. Adding to the value in thenew edition is coverage of: Three new chapters on methods for repeated measurement andother forms of clustered categorical data, including marginalmodels and associated generalized estimating equations (GEE)methods, and mixed models with random effects Stronger emphasis on logistic regression modeling of binaryand multicategory data An appendix showing the use of SAS for conducting nearly allanalyses in the book Prescriptions for how ordinal variables should be treateddifferently than nominal variables Discussion of exact small-sample procedures More than 100 analyses of real data sets to illustrateapplication of the methods, and more than 600 exercises An Instructor's Manual presenting detailed solutions to allthe problems in the book is available from the Wiley editorialdepartment.

Trends and Challenges in Categorical Data Analysis

Maria Kateri,Irini Moustaki
Trends and Challenges in Categorical Data Analysis Book PDF

Author : Maria Kateri,Irini Moustaki
Publisher : Springer Nature
Page : 323 pages
File Size : 46,7 Mb
Release : 2023-07-08
Category : Mathematics
ISBN : 9783031311864

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Trends and Challenges in Categorical Data Analysis by Maria Kateri,Irini Moustaki Pdf

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.

Statistical Methods for Categorical Data Analysis

Daniel Powers,Yu Xie
Statistical Methods for Categorical Data Analysis Book PDF

Author : Daniel Powers,Yu Xie
Publisher : Emerald Group Publishing
Page : 296 pages
File Size : 42,5 Mb
Release : 2008-11-13
Category : Psychology
ISBN : 1781906599

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Statistical Methods for Categorical Data Analysis by Daniel Powers,Yu Xie Pdf

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/

Structural Equation Modeling With AMOS

Barbara M. Byrne
Structural Equation Modeling With AMOS Book PDF

Author : Barbara M. Byrne
Publisher : Routledge
Page : 460 pages
File Size : 52,5 Mb
Release : 2016-06-10
Category : Psychology
ISBN : 9781317633136

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Structural Equation Modeling With AMOS by Barbara M. Byrne Pdf

This bestselling text provides a practical guide to structural equation modeling (SEM) using the Amos Graphical approach. Using clear, everyday language, the text is ideal for those with little to no exposure to either SEM or Amos. The author reviews SEM applications based on actual data taken from her own research. Each chapter "walks" readers through the steps involved (specification, estimation, evaluation, and post hoc modification) in testing a variety of SEM models. Accompanying each application is: an explanation of the issues addressed and a schematic presentation of hypothesized model structure; Amos input and output with interpretations; use of the Amos toolbar icons and pull-down menus; and data upon which the model application was based, together with updated references pertinent to the SEM model tested. Thoroughly updated throughout, the new edition features: All new screen shots featuring Amos Version 23. Descriptions and illustrations of Amos’ new Tables View format which enables the specification of a structural model in spreadsheet form. Key concepts and/or techniques that introduce each chapter. Alternative approaches to model analyses when enabled by Amos thereby allowing users to determine the method best suited to their data. Provides analysis of the same model based on continuous and categorical data (Ch. 5) thereby enabling readers to observe two ways of specifying and testing the same model as well as compare results. All applications based on the Amos graphical mode interface accompanied by more "how to" coverage of graphical techniques unique to Amos. More explanation of key procedures and analyses that address questions posed by readers All application data files are available at www.routledge.com/9781138797031. The two introductory chapters in Section 1 review the fundamental concepts of SEM methodology and a general overview of the Amos program. Section 2 provides single-group analyses applications including two first-order confirmatory factor analytic (CFA) models, one second-order CFA model, and one full latent variable model. Section 3 presents multiple-group analyses applications with two rooted in the analysis of covariance structures and one in the analysis of mean and covariance structures. Two models that are increasingly popular with SEM practitioners, construct validity and testing change over time using the latent growth curve, are presented in Section 4. The book concludes with a review of the use of bootstrapping to address non-normal data and a review of missing (or incomplete) data in Section 5. An ideal supplement for graduate level courses in psychology, education, business, and social and health sciences that cover the fundamentals of SEM with a focus on Amos, this practical text continues to be a favorite of both researchers and practitioners. A prerequisite of basic statistics through regression analysis is recommended but no exposure to either SEM or Amos is required.

Advances in Statistics, Combinatorics and Related Areas

Chandra Gulati
Advances in Statistics Combinatorics and Related Areas Book PDF

Author : Chandra Gulati
Publisher : World Scientific
Page : 409 pages
File Size : 54,7 Mb
Release : 2002
Category : Mathematics
ISBN : 9789812382016

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Advances in Statistics, Combinatorics and Related Areas by Chandra Gulati Pdf

This book is a collection of selected refereed papers presented at the International Conference on Statistics, Combinatorics and Related Areas, and the Eighth International Conference of the Forum for Interdisciplinary Mathematics. It includes contributions from eminent statisticians such as Joe Gani, Clive Granger, Chris Heyde, R Nishii, C R Rao, P K Sen and Sue Wilson. By exploring and investigating deeper, these papers enlarge the reservoir in the represented areas of research, such as bioinformatics, estimating functions, financial statistics, generalized linear models, goodness of fit, image analysis, industrial data analysis, multivariate statistics, neural networks, quasi-likelihood, sample surveys, statistical inference, stochastic models, and time series.

Bayesian Models for Categorical Data

Peter Congdon
Bayesian Models for Categorical Data Book PDF

Author : Peter Congdon
Publisher : John Wiley & Sons
Page : 446 pages
File Size : 51,6 Mb
Release : 2005-12-13
Category : Mathematics
ISBN : 9780470092385

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Bayesian Models for Categorical Data by Peter Congdon Pdf

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.

New Developments in Categorical Data Analysis for the Social and Behavioral Sciences

L. Andries van der Ark,Marcel A. Croon,Klaas Sijtsma
New Developments in Categorical Data Analysis for the Social and Behavioral Sciences Book PDF

Author : L. Andries van der Ark,Marcel A. Croon,Klaas Sijtsma
Publisher : Psychology Press
Page : 274 pages
File Size : 48,9 Mb
Release : 2005-01-15
Category : Business & Economics
ISBN : 9781135704841

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New Developments in Categorical Data Analysis for the Social and Behavioral Sciences by L. Andries van der Ark,Marcel A. Croon,Klaas Sijtsma Pdf

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.

A Course in Categorical Data Analysis

Thomas Leonard
A Course in Categorical Data Analysis Book PDF

Author : Thomas Leonard
Publisher : CRC Press
Page : 204 pages
File Size : 50,8 Mb
Release : 2020-08-26
Category : Mathematics
ISBN : 9781000111569

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A Course in Categorical Data Analysis by Thomas Leonard Pdf

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.

A Course in Categorical Data Analysis

Thomas Leonard
A Course in Categorical Data Analysis Book PDF

Author : Thomas Leonard
Publisher : CRC Press
Page : 208 pages
File Size : 47,6 Mb
Release : 2020-08-26
Category : Mathematics
ISBN : 9781000154658

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A Course in Categorical Data Analysis by Thomas Leonard Pdf

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.

Handbook of Structural Equation Modeling

Rick H. Hoyle
Handbook of Structural Equation Modeling Book PDF

Author : Rick H. Hoyle
Publisher : Guilford Publications
Page : 801 pages
File Size : 53,9 Mb
Release : 2023-02-17
Category : Business & Economics
ISBN : 9781462544646

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Handbook of Structural Equation Modeling by Rick H. Hoyle Pdf

"This accessible volume presents both the mechanics of structural equation modeling (SEM) and specific SEM strategies and applications. The editor, along with an international group of contributors, and editorial advisory board are leading methodologists who have organized the book to move from simpler material to more statistically complex modeling approaches. Sections cover the foundations of SEM; statistical underpinnings, from assumptions to model modifications; steps in implementation, from data preparation through writing the SEM report; and basic and advanced applications, including new and emerging topics in SEM. Each chapter provides conceptually oriented descriptions, fully explicated analyses, and engaging examples that reveal modeling possibilities for use with readers' data. Many of the chapters also include access to data and syntax files at the companion website, allowing readers to try their hands at reproducing the authors' results"--

Applied Missing Data Analysis

Craig K. Enders
Applied Missing Data Analysis Book PDF

Author : Craig K. Enders
Publisher : Guilford Publications
Page : 563 pages
File Size : 45,8 Mb
Release : 2022-08-31
Category : Business & Economics
ISBN : 9781462549863

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Applied Missing Data Analysis by Craig K. Enders Pdf

"The most user-friendly and authoritative resource on missing data has been completely revised to make room for the latest developments that make handling missing data more effective. The second edition includes new methods based on factored regressions, newer model-based imputation strategies, and innovations in Bayesian analysis. State-of-the-art technical literature on missing data is translated into accessible guidelines for applied researchers and graduate students. The second edition takes an even, three-pronged approach to maximum likelihood estimation (MLE), Bayesian estimation as an alternative to MLE, and multiple imputation. Consistently organized chapters explain the rationale and procedural details for each technique and illustrate the analyses with engaging worked-through examples on such topics as young adult smoking, employee turnover, and chronic pain. The companion website includes datasets and analysis examples from the book, up-to-date software information, and other resources. Subject areas/Key words: advanced quantitative methods, management, survey, longitudinal, structural equation modeling, handling, how to handle, incomplete, multivariate, social research, behavioral sciences, statistical techniques, textbooks, seminars, doctoral courses, multiple imputation, models, MCAR, MNAR, Bayesian Audience: Researchers and graduate students in psychology, education, management, family studies, public health, sociology, and political science"--

Bayesian Inference on Complicated Data

Niansheng Tang
Bayesian Inference on Complicated Data Book PDF

Author : Niansheng Tang
Publisher : BoD – Books on Demand
Page : 120 pages
File Size : 55,6 Mb
Release : 2020-07-15
Category : Mathematics
ISBN : 9781838803858

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Bayesian Inference on Complicated Data by Niansheng Tang Pdf

Due to great applications in various fields, such as social science, biomedicine, genomics, and signal processing, and the improvement of computing ability, Bayesian inference has made substantial developments for analyzing complicated data. This book introduces key ideas of Bayesian sampling methods, Bayesian estimation, and selection of the prior. It is structured around topics on the impact of the choice of the prior on Bayesian statistics, some advances on Bayesian sampling methods, and Bayesian inference for complicated data including breast cancer data, cloud-based healthcare data, gene network data, and longitudinal data. This volume is designed for statisticians, engineers, doctors, and machine learning researchers.

Design and Analysis of Long-term Ecological Monitoring Studies

Robert A. Gitzen
Design and Analysis of Long term Ecological Monitoring Studies Book PDF

Author : Robert A. Gitzen
Publisher : Cambridge University Press
Page : 585 pages
File Size : 55,5 Mb
Release : 2012-06-07
Category : Computers
ISBN : 9780521139298

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Design and Analysis of Long-term Ecological Monitoring Studies by Robert A. Gitzen Pdf

Comprehensive and multidisciplinary coverage of fundamental and advanced statistical tools and issues relevant to long-term ecological monitoring.

Assessment of Biodiversity for Improved Forest Planning

Peter Bachmann,Michael Köhl,Risto Päivinen
Assessment of Biodiversity for Improved Forest Planning Book PDF

Author : Peter Bachmann,Michael Köhl,Risto Päivinen
Publisher : Springer Science & Business Media
Page : 604 pages
File Size : 54,5 Mb
Release : 2013-04-17
Category : Technology & Engineering
ISBN : 9789401590068

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Assessment of Biodiversity for Improved Forest Planning by Peter Bachmann,Michael Köhl,Risto Päivinen Pdf

The `Global Biodiversity Strategy' signed in 1992 in Rio de Janeiro, and the resolutions at the Ministerial Conferences on the Protection of Forests in Europe in Strasbourg, 1990, and Helsinki, 1993, commit the signatory states to monitor nationally the state of biodiversity and to sustain the characteristic natural variation in the country. Sustainability and long-term planning are the two terms best describing the philosophy of traditional forest management practices. However, the traditional planning techniques are not primarily developed to maintain sustainability of biodiversity. The gap between the international commitments and the practices in forest assessment and management is obvious. This publication presents experience in methodology for assessing and monitoring the variation of ecosystems and habitats in relation to biodiversity conservation and for integrating biodiversity in regional planning of forest management and land use. The state of the art in the field of natural resource assessments with special reference to forest biodiversity is reviewed, progress in integrating data on biodiversity in forest management planning is presented and the information needs regarding biodiversity conservation and the question to what degree assessment methods for forest biodiversity can be simplified for practical applications are discussed. The book is intended for researchers and practitioners in the field of forest and environmental planning and environmental policies.

Frontiers of Statistical Decision Making and Bayesian Analysis

Ming-Hui Chen,Peter Müller,Dongchu Sun,Keying Ye,Dipak K. Dey
Frontiers of Statistical Decision Making and Bayesian Analysis Book PDF

Author : Ming-Hui Chen,Peter Müller,Dongchu Sun,Keying Ye,Dipak K. Dey
Publisher : Springer Science & Business Media
Page : 631 pages
File Size : 48,7 Mb
Release : 2010-07-24
Category : Mathematics
ISBN : 9781441969446

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Frontiers of Statistical Decision Making and Bayesian Analysis by Ming-Hui Chen,Peter Müller,Dongchu Sun,Keying Ye,Dipak K. Dey Pdf

Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers. This book provides a review of current research challenges and opportunities. While the book can not exhaustively cover all current research areas, it does include some exemplary discussion of most research frontiers. Topics include objective Bayesian inference, shrinkage estimation and other decision based estimation, model selection and testing, nonparametric Bayes, the interface of Bayesian and frequentist inference, data mining and machine learning, methods for categorical and spatio-temporal data analysis and posterior simulation methods. Several major application areas are covered: computer models, Bayesian clinical trial design, epidemiology, phylogenetics, bioinformatics, climate modeling and applications in political science, finance and marketing. As a review of current research in Bayesian analysis the book presents a balance between theory and applications. The lack of a clear demarcation between theoretical and applied research is a reflection of the highly interdisciplinary and often applied nature of research in Bayesian statistics. The book is intended as an update for researchers in Bayesian statistics, including non-statisticians who make use of Bayesian inference to address substantive research questions in other fields. It would also be useful for graduate students and research scholars in statistics or biostatistics who wish to acquaint themselves with current research frontiers.