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Trends and Challenges in Categorical Data Analysis : Statistical Modelling and Interpretation / / edited by Maria Kateri, Irini Moustaki



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Autore: Kateri Maria Visualizza persona
Titolo: Trends and Challenges in Categorical Data Analysis : Statistical Modelling and Interpretation / / edited by Maria Kateri, Irini Moustaki Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023
Edizione: 1st ed. 2023.
Descrizione fisica: 1 online resource (323 pages)
Disciplina: 519.535
Soggetto topico: Statistics
Psychometrics
Epidemiology
Statistical Theory and Methods
Statistics in Life Sciences, Medicine, Health Sciences
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Anàlisi multivariable
Soggetto genere / forma: Llibres electrònics
Altri autori: MoustakiIrini  
Nota di contenuto: Preface -- Chapter 1. Carolyn J. Anderson, Maria Kateri and Irini Moustaki: Log-Linear and Log-Multiplicative Association Models for Categorical Data -- Chapter 2. Peter W. F. Smith: Graphical Models for Categorical Data -- Chapter 3. Tam´as Rudas and Wicher Bergsma: Marginal Models: an Overview -- Chapter 4. Jonathan J Forster and Mark E Grigsby: Bayesian Inference for Multivariate Categorical Data -- Chapter 5. Alan Agresti, Claudia Tarantola and Roberta Varriale: Simple Ways to Interpret Effects in Modeling Binary Data -- Chapter 6. Ioannis Kosmidis: Mean and median bias reduction: A concise review and application to adjacent-categories logit models -- Chapter 7. Jan Gertheiss and Gerhard Tutz: Regularization and Predictor Selection for Ordinal and Categorical Data -- Chapter 8. Mirko Armillotta, Alessandra Luati and Monia Lupparelli: An overview of ARMA-like models for count and binary data -- Chapter 9. Francesco Valentini, Claudia Pigini, and Francesco Bartolucci: Advances in maximum likelihood estimation of fixed-effects binary panel data models.
Sommario/riassunto: 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.
Titolo autorizzato: Trends and Challenges in Categorical Data Analysis  Visualizza cluster
ISBN: 3-031-31186-8
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910734835003321
Lo trovi qui: Univ. Federico II
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Serie: Statistics for Social and Behavioral Sciences, . 2199-7365