Models for Discrete Longitudinal Data

✍ Geert Molenberghs, Geert Verbeke 📂 Library 📅 2005 🏛 Springer 🌐 English

<P>This book provides a comprehensive treatment on modeling approaches for non-Gaussian repeated measures, possibly subject to incompleteness. The authors begin with models for the full marginal distribution of the outcome vector. This allows model fitting to be based on maximum likelihood principle

Models for Discrete Longitudinal Data (S

📁 Models for Discrete Longitudinal Data (Springer Series in Statistics)

✍ Geert Molenberghs, Geert Verbeke 📂 Library 📅 2005 🏛 Springer 🌐 English

The linear mixed model has become the main parametric tool for the analysis of continuous longitudinal data, as the authors discussed in their 2000 book. Without putting too much emphasis on software, the book shows how the different approaches can be implemented within the SAS software package.

Models for Discrete Longitudinal Data (S

📁 Models for Discrete Longitudinal Data (Springer Series in Statistics)

✍ Geert Molenberghs, Geert Verbeke 📂 Library 📅 2005 🏛 Springer 🌐 English

<p><span>This book provides a comprehensive treatment on modeling approaches for non-Gaussian repeated measures, possibly subject to incompleteness. Without putting too much emphasis on software, the book shows how the different approaches can be implemented within the SAS software package. The text

Models for intensive longitudinal data

📁 Models for intensive longitudinal data

✍ Theodore A. Walls, Joseph L. Schafer 📂 Library 📅 2006 🏛 Oxford University Press, USA 🌐 English

Rapid technological advances in devices used for data collection have led to the emergence of a new class of longitudinal data: intensive longitudinal data (ILD). Behavioral scientific studies now frequently utilize handheld computers, beepers, web interfaces, and other technological tools for colle

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