Linear Mixed Models for Longitudinal Data

Linear Mixed Models for Longitudinal Dat

📁 Linear Mixed Models for Longitudinal Data

✍ Geert Verbeke, Geert Molenberghs 📂 Library 📅 2001 🏛 Springer 🌐 English

This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance

Linear Mixed Models for Longitudinal Dat

📁 Linear Mixed Models for Longitudinal Data

✍ Geert Verbeke, Geert Molenberghs 📂 Library 📅 2000 🏛 Springer 🌐 English

This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance

Linear Mixed Models for Longitudinal Dat

📁 Linear Mixed Models for Longitudinal Data

✍ Geert Molenberghs, Geert Verbeke (auth.) 📂 Library 📅 2000 🏛 Springer-Verlag New York 🌐 English

This paperback edition is a reprint of the 2000 edition.This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, suc

Linear Mixed Models for Longitudinal Dat

📁 Linear Mixed Models for Longitudinal Data

✍ Geert Verbeke, Geert Molenberghs 📂 Library 📅 2000 🏛 Springer 🌐 English

This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this book puts major emphasis on exploratory data analysis for all aspects of the model. Several variations to the conventional linear mixed model are discussed. Most anal

Longitudinal Data Analysis: Autoregressi

📁 Longitudinal Data Analysis: Autoregressive Linear Mixed Effects Models

✍ Ikuko Funatogawa, Takashi Funatogawa 📂 Library 📅 2018 🏛 Springer Singapore 🌐 English

This book provides a new analytical approach for dynamic data repeatedly measured from multiple subjects over time. Random effects account for differences across subjects. Auto-regression in response itself is often used in time series analysis. In longitudinal data analysis, a static mixed effec

Dynamic Mixed Models for Familial Longit

📁 Dynamic Mixed Models for Familial Longitudinal Data

✍ Brajendra C. Sutradhar (auth.) 📂 Library 📅 2011 🏛 Springer-Verlag New York 🌐 English

This book provides a theoretical foundation for the analysis of discrete data such as count and binary data in the longitudinal setup. Unlike the existing books, this book uses a class of auto-correlation structures to model the longitudinal correlations for the repeated discrete data that acc