Trends and Challenges in Categorical Data Analysis

 
Trends and Challenges in Categorical Data Analysis
Free Download Trends and Challenges in Categorical Data Analysis: Statistical Modelling and Interpretation
English | 2023 | ISBN: 303131185X | 315 Pages | PDF EPUB (True) | 18 MB
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.


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Applied Categorical and Count Data Analysis (Chapman & Hall CRC Texts in Statistical Science)

 
Applied Categorical and Count Data Analysis (Chapman & Hall CRC Texts in Statistical Science)
Free Download Applied Categorical and Count Data Analysis (Chapman & Hall CRC Texts in Statistical Science) by Wan Tang, Hua He, Xin M. Tu
English | April 6, 2023 | ISBN: 0367568276 | 394 pages | MOBI | 1.85 Mb
Developed from the authors' graduate-level biostatistics course, Applied Categorical and Count Data Analysis, Second Edition explains how to perform the statistical analysis of discrete data, including categorical and count outcomes. The authors have been teaching categorical data analysis courses at the University of Rochester and Tulane University for more than a decade. This book embodies their decade-long experience and insight in teaching and applying statistical models for categorical and count data. The authors describe the basic ideas underlying each concept, model, and approach to give readers a good grasp of the fundamentals of the methodology without relying on rigorous mathematical arguments.


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