Hierarchical Quantile Modeling

Theory, Methodology and Applications de

Éditeur :

EDP Sciences


Collection :

Current Natural Sciences

Paru le : 2024-11-07

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Description
This book offers a concise and comprehensive introduction to Hierarchical Quantile Modeling, a modern statistical methodology that extends traditional hierarchical models and quantile regression techniques to analyze complex data structures often found in fields like biology, economics, and education. Unlike classic models, Hierarchical Quantile Modeling accommodates heteroscedasticity and nonparametric relationships, allowing for a detailed study of the entire conditional distribution of a response variable. The book is structured in four parts: an introduction to hierarchical modeling, a detailed look at quantile regression, an in-depth exploration of Hierarchical Quantile Modeling, and practical applications using real-world hierarchical, repeated, and clustered data. Drawing on the author’s decade-long experience in research and teaching, this guide is ideal for graduate students, researchers, and practitioners. It includes examples and software guidance using R, S-plus, SAS, and SPSS, making it a valuable resource for anyone interested in advanced statistical analysis.
Pages
752 pages
Collection
Current Natural Sciences
Parution
2024-11-07
Marque
EDP Sciences
EAN papier
9782759837205
EAN PDF SANS DRM
9782759837205

Informations sur l'ebook
Prix
136,99 €