Linear Mixed Models for Longitudinal Data

• Main Authors: Verbeke, Geert (Author), Molenberghs, Geert (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: New York, NY : Springer New York, 2000.
• Series: Springer Series in Statistics,
• Subjects: Mathematics.; Mathematical models.; Probabilities.; Statistics.; Mathematical Modeling and Industrial Mathematics.; Probability Theory and Stochastic Processes.; Statistical Theory and Methods.

Table of Contents:

• Examples
• A Model for Longitudinal Data
• Exploratory Data Analysis
• Estimation of the Marginal Model
• Inference for the Marginal Model
• Inference for the Random Effects
• Fitting Linear Mixed Models with SAS
• General Guidelines for Model Building
• Exploring Serial Correlation
• Local Influence for the Linear Mixed Model
• The Heterogeneity Model
• Conditional Linear Mixed Models
• Exploring Incomplete Data
• Joint Modeling of Measurements and Missingness
• Simple Missing Data Methods
• Selection Models
• Pattern-Mixture Models
• Sensitivity Analysis for Selection Models
• Sensitivity Analysis for Pattern-Mixture Models
• How Ignorable Is Missing At Random ?
• The Expectation-Maximization Algorithm
• Design Considerations
• Case Studies.