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  • 1
    Online Resource
    Online Resource
    Cham :Springer International Publishing, | Cham :Springer.
    UID:
    edoccha_BV049083029
    Format: 1 Online-Ressource (XII, 315 p. 57 illus., 11 illus. in color).
    Edition: 1st ed. 2023
    ISBN: 978-3-031-31186-4
    Series Statement: Statistics for Social and Behavioral Sciences
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-31185-7
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-31187-1
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-31188-8
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    Cham :Springer International Publishing, | Cham :Springer.
    UID:
    almafu_BV049083029
    Format: 1 Online-Ressource (XII, 315 p. 57 illus., 11 illus. in color).
    Edition: 1st ed. 2023
    ISBN: 978-3-031-31186-4
    Series Statement: Statistics for Social and Behavioral Sciences
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-31185-7
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-31187-1
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-31188-8
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Online Resource
    Online Resource
    Cham :Springer International Publishing, | Cham :Springer.
    UID:
    edocfu_BV049083029
    Format: 1 Online-Ressource (XII, 315 p. 57 illus., 11 illus. in color).
    Edition: 1st ed. 2023
    ISBN: 978-3-031-31186-4
    Series Statement: Statistics for Social and Behavioral Sciences
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-31185-7
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-31187-1
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-31188-8
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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  • 4
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Imprint: Springer
    UID:
    gbv_1852346418
    Format: 1 Online-Ressource(XII, 315 p. 57 illus., 11 illus. in color.)
    Edition: 1st ed. 2023.
    ISBN: 9783031311864
    Series Statement: Statistics for Social and Behavioral Sciences
    Content: 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.
    Content: 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.
    Additional Edition: ISBN 9783031311857
    Additional Edition: ISBN 9783031311871
    Additional Edition: ISBN 9783031311888
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783031311857
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783031311871
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783031311888
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 5
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer
    UID:
    b3kat_BV049083029
    Format: 1 Online-Ressource (XII, 315 p. 57 illus., 11 illus. in color)
    Edition: 1st ed. 2023
    ISBN: 9783031311864
    Series Statement: Statistics for Social and Behavioral Sciences
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-31185-7
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-31187-1
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-31188-8
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 6
    UID:
    almahu_9949535971802882
    Format: XII, 315 p. 57 illus., 11 illus. in color. , online resource.
    Edition: 1st ed. 2023.
    ISBN: 9783031311864
    Series Statement: Statistics for Social and Behavioral Sciences,
    Content: 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.
    Note: 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.
    In: Springer Nature eBook
    Additional Edition: Printed edition: ISBN 9783031311857
    Additional Edition: Printed edition: ISBN 9783031311871
    Additional Edition: Printed edition: ISBN 9783031311888
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
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