Identifiability Of Discrete Hierarchical Models With One Latent Variable

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Bayesian Hierarchical Models

Author : Peter D. Congdon
Publisher : CRC Press
ISBN 13 : 0429532903
Total Pages : 487 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Bayesian Hierarchical Models by : Peter D. Congdon

Download or read book Bayesian Hierarchical Models written by Peter D. Congdon and published by CRC Press. This book was released on 2019-09-16 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where parameters can be treated as random collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian hierarchical methods. The new edition is a revision of the book Applied Bayesian Hierarchical Methods. It maintains a focus on applied modelling and data analysis, but now using entirely R-based Bayesian computing options. It has been updated with a new chapter on regression for causal effects, and one on computing options and strategies. This latter chapter is particularly important, due to recent advances in Bayesian computing and estimation, including the development of rjags and rstan. It also features updates throughout with new examples. The examples exploit and illustrate the broader advantages of the R computing environment, while allowing readers to explore alternative likelihood assumptions, regression structures, and assumptions on prior densities. Features: Provides a comprehensive and accessible overview of applied Bayesian hierarchical modelling Includes many real data examples to illustrate different modelling topics R code (based on rjags, jagsUI, R2OpenBUGS, and rstan) is integrated into the book, emphasizing implementation Software options and coding principles are introduced in new chapter on computing Programs and data sets available on the book’s website

Applied Bayesian Hierarchical Methods

Author : Peter D. Congdon
Publisher : CRC Press
ISBN 13 : 1584887214
Total Pages : 606 pages
Book Rating : 4.5/5 (848 download)

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Book Synopsis Applied Bayesian Hierarchical Methods by : Peter D. Congdon

Download or read book Applied Bayesian Hierarchical Methods written by Peter D. Congdon and published by CRC Press. This book was released on 2010-05-19 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of Markov chain Monte Carlo (MCMC) methods for estimating hierarchical models involves complex data structures and is often described as a revolutionary development. An intermediate-level treatment of Bayesian hierarchical models and their applications, Applied Bayesian Hierarchical Methods demonstrates the advantages of a Bayesian approach

Aspects of Uncertainty

Author : Adrian F. M. Smith
Publisher :
ISBN 13 :
Total Pages : 428 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Aspects of Uncertainty by : Adrian F. M. Smith

Download or read book Aspects of Uncertainty written by Adrian F. M. Smith and published by . This book was released on 1994-09-13 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Throughout his career Dennis Lindley has insisted on thinking things through from first principles and on basing developments on firm, logical foundations. Although his fundamental contributions to Bayesian statistics and decision theory are universally recognised, it is less well known that he arrived at the Bayesian position as a result of seeking to establish a rigorous axiomatic justification for classical statistical procedures.

Data Analysis Using Regression and Multilevel/Hierarchical Models

Author : Andrew Gelman
Publisher : Cambridge University Press
ISBN 13 : 9780521686891
Total Pages : 654 pages
Book Rating : 4.6/5 (868 download)

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Book Synopsis Data Analysis Using Regression and Multilevel/Hierarchical Models by : Andrew Gelman

Download or read book Data Analysis Using Regression and Multilevel/Hierarchical Models written by Andrew Gelman and published by Cambridge University Press. This book was released on 2007 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

Latent Variable Models

Author : John C. Loehlin
Publisher : Psychology Press
ISBN 13 : 1135614342
Total Pages : 303 pages
Book Rating : 4.1/5 (356 download)

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Book Synopsis Latent Variable Models by : John C. Loehlin

Download or read book Latent Variable Models written by John C. Loehlin and published by Psychology Press. This book was released on 2004-05-20 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. This approach helps less mathematically inclined students grasp the underlying relationships between path analysis, factor analysis, and structural equation modeling more easily. A few sections of the book make use of elementary matrix algebra. An appendix on the topic is provided for those who need a review. The author maintains an informal style so as to increase the book's accessibility. Notes at the end of each chapter provide some of the more technical details. The book is not tied to a particular computer program, but special attention is paid to LISREL, EQS, AMOS, and Mx. New in the fourth edition of Latent Variable Models: *a data CD that features the correlation and covariance matrices used in the exercises; *new sections on missing data, non-normality, mediation, factorial invariance, and automating the construction of path diagrams; and *reorganization of chapters 3-7 to enhance the flow of the book and its flexibility for teaching. Intended for advanced students and researchers in the areas of social, educational, clinical, industrial, consumer, personality, and developmental psychology, sociology, political science, and marketing, some prior familiarity with correlation and regression is helpful.

Latent Markov Models for Longitudinal Data

Author : Francesco Bartolucci
Publisher : CRC Press
ISBN 13 : 1466583711
Total Pages : 253 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Latent Markov Models for Longitudinal Data by : Francesco Bartolucci

Download or read book Latent Markov Models for Longitudinal Data written by Francesco Bartolucci and published by CRC Press. This book was released on 2012-10-29 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing on the authors' extensive research in the analysis of categorical longitudinal data, this book focuses on the formulation of latent Markov models and the practical use of these models. It demonstrates how to use the models in three types of analysis, with numerous examples illustrating how latent Markov models are used in economics, education, sociology, and other fields. The R and MATLAB routines used for the examples are available on the authors' website.

Handbook of Choice Modelling

Author : Stephane Hess
Publisher : Edward Elgar Publishing
ISBN 13 : 1800375638
Total Pages : 797 pages
Book Rating : 4.8/5 (3 download)

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Book Synopsis Handbook of Choice Modelling by : Stephane Hess

Download or read book Handbook of Choice Modelling written by Stephane Hess and published by Edward Elgar Publishing. This book was released on 2024-06-05 with total page 797 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thoroughly revised second edition Handbook provides an authoritative and in-depth overview of choice modelling, covering essential topics range from data collection through model specification and estimation to analysis and use of results. It aptly emphasises the broad relevance of choice modelling when applied to a multitude of fields, including but not limited to transport, marketing, health and environmental economics.

Enabling AI Applications in Data Science

Author : Aboul-Ella Hassanien
Publisher : Springer Nature
ISBN 13 : 3030520676
Total Pages : 644 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Enabling AI Applications in Data Science by : Aboul-Ella Hassanien

Download or read book Enabling AI Applications in Data Science written by Aboul-Ella Hassanien and published by Springer Nature. This book was released on 2020-09-23 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a detailed overview of the latest developments and applications in the field of artificial intelligence and data science. AI applications have achieved great accuracy and performance with the help of developments in data processing and storage. It has also gained strength through the amount and quality of data which is the main nucleus of data science. This book aims to provide the latest research findings in the field of artificial intelligence with data science.

Discrete Choice Methods with Simulation

Author : Kenneth Train
Publisher : Cambridge University Press
ISBN 13 : 0521766559
Total Pages : 399 pages
Book Rating : 4.5/5 (217 download)

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Book Synopsis Discrete Choice Methods with Simulation by : Kenneth Train

Download or read book Discrete Choice Methods with Simulation written by Kenneth Train and published by Cambridge University Press. This book was released on 2009-07-06 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.

Multidimensional Item Response Theory

Author : M.D. Reckase
Publisher : Springer Science & Business Media
ISBN 13 : 0387899766
Total Pages : 355 pages
Book Rating : 4.3/5 (878 download)

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Book Synopsis Multidimensional Item Response Theory by : M.D. Reckase

Download or read book Multidimensional Item Response Theory written by M.D. Reckase and published by Springer Science & Business Media. This book was released on 2009-07-07 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: First thorough treatment of multidimensional item response theory Description of methods is supported by numerous practical examples Describes procedures for multidimensional computerized adaptive testing

Bayesian Statistical Modelling

Author : Peter Congdon
Publisher : John Wiley & Sons
ISBN 13 : 0470035935
Total Pages : 596 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Bayesian Statistical Modelling by : Peter Congdon

Download or read book Bayesian Statistical Modelling written by Peter Congdon and published by John Wiley & Sons. This book was released on 2007-04-04 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian methods combine the evidence from the data at hand with previous quantitative knowledge to analyse practical problems in a wide range of areas. The calculations were previously complex, but it is now possible to routinely apply Bayesian methods due to advances in computing technology and the use of new sampling methods for estimating parameters. Such developments together with the availability of freeware such as WINBUGS and R have facilitated a rapid growth in the use of Bayesian methods, allowing their application in many scientific disciplines, including applied statistics, public health research, medical science, the social sciences and economics. Following the success of the first edition, this reworked and updated book provides an accessible approach to Bayesian computing and analysis, with an emphasis on the principles of prior selection, identification and the interpretation of real data sets. The second edition: Provides an integrated presentation of theory, examples, applications and computer algorithms. Discusses the role of Markov Chain Monte Carlo methods in computing and estimation. Includes a wide range of interdisciplinary applications, and a large selection of worked examples from the health and social sciences. Features a comprehensive range of methodologies and modelling techniques, and examines model fitting in practice using Bayesian principles. Provides exercises designed to help reinforce the reader’s knowledge and a supplementary website containing data sets and relevant programs. Bayesian Statistical Modelling is ideal for researchers in applied statistics, medical science, public health and the social sciences, who will benefit greatly from the examples and applications featured. The book will also appeal to graduate students of applied statistics, data analysis and Bayesian methods, and will provide a great source of reference for both researchers and students. Praise for the First Edition: “It is a remarkable achievement to have carried out such a range of analysis on such a range of data sets. I found this book comprehensive and stimulating, and was thoroughly impressed with both the depth and the range of the discussions it contains.” – ISI - Short Book Reviews “This is an excellent introductory book on Bayesian modelling techniques and data analysis” – Biometrics “The book fills an important niche in the statistical literature and should be a very valuable resource for students and professionals who are utilizing Bayesian methods.” – Journal of Mathematical Psychology

Models for Discrete Longitudinal Data

Author : Geert Molenberghs
Publisher : Springer Science & Business Media
ISBN 13 : 9780387251448
Total Pages : 720 pages
Book Rating : 4.2/5 (514 download)

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Book Synopsis Models for Discrete Longitudinal Data by : Geert Molenberghs

Download or read book Models for Discrete Longitudinal Data written by Geert Molenberghs and published by Springer Science & Business Media. This book was released on 2006-08-30 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: The linear mixed model has become the main parametric tool for the analysis of continuous longitudinal data, as the authors discussed in their 2000 book. Without putting too much emphasis on software, the book shows how the different approaches can be implemented within the SAS software package. The authors received the American Statistical Association's Excellence in Continuing Education Award based on short courses on longitudinal and incomplete data at the Joint Statistical Meetings of 2002 and 2004.

Generalized Latent Variable Modeling

Author : Anders Skrondal
Publisher : CRC Press
ISBN 13 : 1135443408
Total Pages : 523 pages
Book Rating : 4.1/5 (354 download)

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Book Synopsis Generalized Latent Variable Modeling by : Anders Skrondal

Download or read book Generalized Latent Variable Modeling written by Anders Skrondal and published by CRC Press. This book was released on 2004-05-11 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and contrast a wide range of estimation and prediction methods from biostatistics, psychometrics, econometrics, and statistics. They present exciting and realistic applications that demonstrate how researchers can use latent variable modeling to solve concrete problems in areas as diverse as medicine, economics, and psychology. The examples considered include many nonstandard response types, such as ordinal, nominal, count, and survival data. Joint modeling of mixed responses, such as survival and longitudinal data, is also illustrated. Numerous displays, figures, and graphs make the text vivid and easy to read. About the authors: Anders Skrondal is Professor and Chair in Social Statistics, Department of Statistics, London School of Economics, UK Sophia Rabe-Hesketh is a Professor of Educational Statistics at the Graduate School of Education and Graduate Group in Biostatistics, University of California, Berkeley, USA.

Longitudinal Structural Equation Modeling

Author : Jason T. Newsom
Publisher : Routledge
ISBN 13 : 1317975359
Total Pages : 437 pages
Book Rating : 4.3/5 (179 download)

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Book Synopsis Longitudinal Structural Equation Modeling by : Jason T. Newsom

Download or read book Longitudinal Structural Equation Modeling written by Jason T. Newsom and published by Routledge. This book was released on 2015-06-19 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive resource reviews structural equation modeling (SEM) strategies for longitudinal data to help readers see which modeling options are available for which hypotheses. The author demonstrates how SEM is related to other longitudinal data techniques throughout. By exploring connections between models, readers gain a better understanding of when to choose one analysis over another. The book explores basic models to sophisticated ones including the statistical and conceptual underpinnings that are the building blocks of the analyses. Accessibly written, research examples from the behavioral and social sciences and results interpretations are provided throughout. The emphasis is on concepts and practical guidance for applied research rather than on mathematical proofs. New terms are highlighted and defined in the glossary. Figures are included for every model along with detailed discussions of model specification and implementation issues. Each chapter also includes examples of each model type, comment sections that provide practical guidance, model extensions, and recommended readings. Highlights include: Covers the major SEM approaches to longitudinal analysis in one resource. Explores connections between longitudinal SEM models to enhance integration. Numerous examples that help readers match research questions to appropriate analyses and interpret results. Reviews practical issues related to model specification and estimation to reinforce connections. Analyzes continuous and discrete (binary and ordinal) variables throughout for breadth not found in other sources. Reviews key SEM concepts for those who need a refresher (Ch. 1). Emphasizes how to apply and interpret each model through realistic data examples. Provides the book’s data sets at www.longitudinalsem.com along with the Mplus and R-lavaan syntax used to generate the results. Introduces the LISREL notation system used throughout (Appendix A). The chapters can be read out of order but it is best to read chapters 1 – 4 first because most of the later chapters refer back to them. The book opens with a review of latent variables and analysis of binary and ordinal variables. Chapter 2 applies this information to assessing longitudinal measurement invariance. SEM tests of dependent means and proportions over time points are explored in Chapter 3, and stability and change, difference scores, and lagged regression are covered in Chapter 4. The remaining chapters are each devoted to one major type of longitudinal SEM -- repeated measures analysis models, full cross-lagged panel models and simplex models, modeling stability with state-trait models, linear and nonlinear growth curve models, latent difference score models, latent transition analysis, time series analysis, survival analysis, and attrition. Missing data is discussed in the context of many of the preceding models in Chapter 13. Ideal for graduate courses on longitudinal (data) analysis, advanced SEM, longitudinal SEM, and/or advanced data (quantitative) analysis taught in the behavioral, social, and health sciences, this text also appeals to researchers in these fields. Intended for those without an extensive math background, prerequisites include familiarity with basic SEM. Matrix algebra is avoided in all but a few places.

Handbook of Item Response Theory

Author : Wim J. van der Linden
Publisher : CRC Press
ISBN 13 : 1351645455
Total Pages : 1584 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Handbook of Item Response Theory by : Wim J. van der Linden

Download or read book Handbook of Item Response Theory written by Wim J. van der Linden and published by CRC Press. This book was released on 2018-02-19 with total page 1584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing on the work of 75 internationally acclaimed experts in the field, Handbook of Item Response Theory, Three-Volume Set presents all major item response models, classical and modern statistical tools used in item response theory (IRT), and major areas of applications of IRT in educational and psychological testing, medical diagnosis of patient-reported outcomes, and marketing research. It also covers CRAN packages, WinBUGS, Bilog MG, Multilog, Parscale, IRTPRO, Mplus, GLLAMM, Latent Gold, and numerous other software tools. A full update of editor Wim J. van der Linden and Ronald K. Hambleton’s classic Handbook of Modern Item Response Theory, this handbook has been expanded from 28 chapters to 85 chapters in three volumes. The three volumes are thoroughly edited and cross-referenced, with uniform notation, format, and pedagogical principles across all chapters. Each chapter is self-contained and deals with the latest developments in IRT.

Bayesian Statistics and Marketing

Author : Peter E. Rossi
Publisher : John Wiley & Sons
ISBN 13 : 0470863684
Total Pages : 368 pages
Book Rating : 4.4/5 (78 download)

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Book Synopsis Bayesian Statistics and Marketing by : Peter E. Rossi

Download or read book Bayesian Statistics and Marketing written by Peter E. Rossi and published by John Wiley & Sons. This book was released on 2012-05-14 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decade has seen a dramatic increase in the use of Bayesian methods in marketing due, in part, to computational and modelling breakthroughs, making its implementation ideal for many marketing problems. Bayesian analyses can now be conducted over a wide range of marketing problems, from new product introduction to pricing, and with a wide variety of different data sources. Bayesian Statistics and Marketing describes the basic advantages of the Bayesian approach, detailing the nature of the computational revolution. Examples contained include household and consumer panel data on product purchases and survey data, demand models based on micro-economic theory and random effect models used to pool data among respondents. The book also discusses the theory and practical use of MCMC methods. Written by the leading experts in the field, this unique book: Presents a unified treatment of Bayesian methods in marketing, with common notation and algorithms for estimating the models. Provides a self-contained introduction to Bayesian methods. Includes case studies drawn from the authors’ recent research to illustrate how Bayesian methods can be extended to apply to many important marketing problems. Is accompanied by an R package, bayesm, which implements all of the models and methods in the book and includes many datasets. In addition the book’s website hosts datasets and R code for the case studies. Bayesian Statistics and Marketing provides a platform for researchers in marketing to analyse their data with state-of-the-art methods and develop new models of consumer behaviour. It provides a unified reference for cutting-edge marketing researchers, as well as an invaluable guide to this growing area for both graduate students and professors, alike.

Latent Trait and Latent Class Models

Author : R. Langeheine
Publisher : Springer Science & Business Media
ISBN 13 : 1475756445
Total Pages : 309 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Latent Trait and Latent Class Models by : R. Langeheine

Download or read book Latent Trait and Latent Class Models written by R. Langeheine and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is based on an international conference held at the Institute for Science Education (IPN) in Kiel in August 1985. The IPN is a national research institute for science education of the Federal Republic of Germany associated with the University of Kiel. The aim of this conference-to treat latent trait and latent class models under comparative points of view as well as under application aspects-was realized in many stimulating contributions and very different ways. We asked the authors of these papers to work out their contributions for publication here, not only because many of the papers present new material, but also because the time is ripe for a comprehen sive volume, working up the widespread literature of the past ten years in this field. We have tried to compile a volume that will be of interest to statistically oriented researchers in a variety of disciplines, including psychology, sociology, education, political science, epidemiology, and the like. Although the chapters assume a reasonably high level of methodo logical sophistication, we hope that the book will find its way into advanced courses in the above fields. We are grateful to the IPN for organizing the conference, to our contributors for their untiring efforts in revising their chapters for publication, and to the staff of Plenum Publishing Corporation for helping to make this book a reality.