Trends and Challenges in Categorical Data Analysis Statistical Modelling and Interpretation /
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 g...
שמור ב:
| מחבר תאגידי: | |
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| מחברים אחרים: | , |
| פורמט: | אלקטרוני ספר אלקטרוני |
| שפה: | אנגלית |
| יצא לאור: |
Cham :
Springer International Publishing : Imprint: Springer,
2023.
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| מהדורה: | 1st ed. 2023. |
| סדרה: | Statistics for Social and Behavioral Sciences,
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| נושאים: | |
| גישה מקוונת: | https://doi.org/10.1007/978-3-031-31186-4 |
| תגים: |
הוספת תג
אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!
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תוכן הענינים:
- 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.