Latent Class Marginal Models For The Analysis Of Cross Classified Categorical Data
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Latent Class Marginal Models For The Analysis Of Cross Classified Categorical Data
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Author : Ilsoon Yang
language : en
Publisher:
Release Date : 1996
Latent Class Marginal Models For The Analysis Of Cross Classified Categorical Data written by Ilsoon Yang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Latent structure analysis categories.
The Analysis Of Cross Classified Categorical Data
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Author : Stephen E. Fienberg
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-08-06
The Analysis Of Cross Classified Categorical Data written by Stephen E. Fienberg and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-06 with Mathematics categories.
A variety of biological and social science data come in the form of cross-classified tables of counts, commonly referred to as contingency tables. Until recent years the statistical and computational techniques available for the analysis of cross-classified data were quite limited. This book presents some of the recent work on the statistical analysis of cross-classified data using longlinear models, especially in the multidimensional situation.
Lectures On Advanced Topics In Categorical Data Analysis
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Author : Tamás Rudas
language : en
Publisher: Springer Nature
Release Date : 2024-12-16
Lectures On Advanced Topics In Categorical Data Analysis written by Tamás Rudas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-16 with Mathematics categories.
This book continues the mission of the previous text by the author, Lectures on Categorical Data Analysis, by expanding on the introductory concepts from that volume and providing a mathematically rigorous presentation of advanced topics and current research in statistical techniques which can be applied in the social, political, behavioral, and life sciences. It presents an intuitive and unified discussion of an array of themes in categorical data analysis, and the emphasis on structure over stochastics renders many of the methods applicable in machine learning environments and for the analysis of big data. The book focuses on graphical models, their application in causal analysis, the analytical properties of parameterizations of multivariate discrete distributions, marginal models, and coordinate-free relational models. To guide the readers in future research, the volume provides references to original papers and also offers detailed proofs of most of the significant results. Like the previous volume, it features exercises and research questions, making it appropriate for graduate students, as well as for active researchers.
The Statistical Analysis Of Categorical Data
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Author : Erling B. Andersen
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
The Statistical Analysis Of Categorical Data written by Erling B. Andersen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.
The aim of this book is to give an up to date account of the most commonly uses statist i cal models for categoriCal data. The emphasis is on the connection between theory and appIications to real data sets. The book only covers models for categorical data. Various n:t0dels 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 eises. 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 in chapter 3 of basic properties of exponential families and the parametric multinomial distribution is made as mathematical preeise as possible without going into mathematical details and leaving out most proofs.
Simultaneous Modeling Of Marginal Distributions And Log Multiplicative Associations For Ordered Multivariate Categorical Data
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Author : Susan Marie Minick
language : en
Publisher:
Release Date : 1997
Simultaneous Modeling Of Marginal Distributions And Log Multiplicative Associations For Ordered Multivariate Categorical Data written by Susan Marie Minick and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with categories.
Loglinear Models With Latent Variables
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Author : Jacques A. Hagenaars
language : en
Publisher: SAGE
Release Date : 1993-08-09
Loglinear Models With Latent Variables written by Jacques A. Hagenaars and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-08-09 with Mathematics categories.
Sociologists with a quantitative bent will doubtless find it useful. . . . well-written, with a wealth of explanation. . . --Dougal Hutchison in Educational Research "Loglinear Models with Latent Variables, by Jacques A. Hagenaars, is a timely contribution to the literature that serves to inform researchers of the richness of loglinear approaches to analyzing latent categorical variables. . . . The author provides a clear exposition of the loglinear model." --Scott L. Hershberger in Structural Equation Modeling Since the 1980s, the loglinear model has become the dominant form of categorical data analysis as researchers have expanded it into new directions. Jacques A. Hagenaars′ book shows researchers the applications of one of these new developments--how uniting ordinary loglinear analysis and latent class analysis into a general loglinear model with latent variables can result in a modified LISREL approach. This modified LISREL model will enable researchers to analyze categorical data in the same way that they have been able to use LISREL to analyze continuous data. Beginning with an introduction to ordinary loglinear modeling and standard latent class analysis, Hagenaars explains the general principles of loglinear modeling with latent variables; the application of loglinear models with latent variables as a causal model, as well as a tool for the analysis of categorical longitudinal data; the strengths and limitations of this technique; and lastly, a summary of computer programs that are available for executing this technique.
Contingency Table Analysis
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Author : Maria Kateri
language : en
Publisher: Springer
Release Date : 2014-05-17
Contingency Table Analysis written by Maria Kateri and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-17 with Mathematics categories.
Contingency tables arise in diverse fields, including life sciences, education, social and political sciences, notably market research and opinion surveys. Their analysis plays an essential role in gaining insight into structures of the quantities under consideration and in supporting decision making. Combining both theory and applications, this book presents models and methods for the analysis of two- and multidimensional-contingency tables. An excellent reference for advanced undergraduates, graduate students, and practitioners in statistics as well as biosciences, social sciences, education, and economics, the work may also be used as a textbook for a course on categorical data analysis. Prerequisites include basic background on statistical inference and knowledge of statistical software packages.
Models For Discreet Data
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Author : Daniel Zelterman
language : en
Publisher: Oxford University Press, USA
Release Date : 1999-01-21
Models For Discreet Data written by Daniel Zelterman and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-01-21 with Mathematics categories.
Discrete or count data arise in experiments where the outcome variables are the numbers of individuals classified into unique, non-overlapping categories. This revised edition describes the statistical models used in the analysis and summary of such data, and provides a sound introduction to the subject for graduate students and practitioners needing a review of the methodology. With many numerical examples throughout, it includes topics not covered in depth elsewhere, such as thenegative multinomial distribution; the many forms of the hypergeometric distribution; and coordinate free models. A detailed treatment of sample size estimation and power are given in terms of both exact inference and asymptotic, non-central chi-squared methods. A new section covering Poissonregression has also been included. An important feature of this book, missing elsewhere, is the integration of the software into the text.Many more exercises are provided (including 84% more applied exercises) than in the previous edition, helping consolidate the reader's understanding of all subjects covered, and making the book highly suitable for use in a classroom setting. Several new datasets, mostly from the health and medical sector, are discussed, including previously unpublished data from a study of Tourette's Syndrome in children.
Advances In Latent Class Analysis
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Author : Gregory R. Hancock
language : en
Publisher: IAP
Release Date : 2019-05-01
Advances In Latent Class Analysis written by Gregory R. Hancock and has been published by IAP this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-01 with Education categories.
What is latent class analysis? If you asked that question thirty or forty years ago you would have gotten a different answer than you would today. Closer to its time of inception, latent class analysis was viewed primarily as a categorical data analysis technique, often framed as a factor analysis model where both the measured variable indicators and underlying latent variables are categorical. Today, however, it rests within much broader mixture and diagnostic modeling framework, integrating measured and latent variables that may be categorical and/or continuous, and where latent classes serve to define the subpopulations for whom many aspects of the focal measured and latent variable model may differ. For latent class analysis to take these developmental leaps required contributions that were methodological, certainly, as well as didactic. Among the leaders on both fronts was C. Mitchell “Chan” Dayton, at the University of Maryland, whose work in latent class analysis spanning several decades helped the method to expand and reach its current potential. The current volume in the Center for Integrated Latent Variable Research (CILVR) series reflects the diversity that is latent class analysis today, celebrating work related to, made possible by, and inspired by Chan’s noted contributions, and signaling the even more exciting future yet to come.
Handbook Of Statistical Modeling For The Social And Behavioral Sciences
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Author : G. Arminger
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Handbook Of Statistical Modeling For The Social And Behavioral Sciences written by G. Arminger and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Psychology categories.
Contributors thoroughly survey the most important statistical models used in empirical reserch in the social and behavioral sciences. Following a common format, each chapter introduces a model, illustrates the types of problems and data for which the model is best used, provides numerous examples that draw upon familiar models or procedures, and includes material on software that can be used to estimate the models studied. This handbook will aid researchers, methodologists, graduate students, and statisticians to understand and resolve common modeling problems.