Linear Mixed Models for Longitudinal Data

Introduction. 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 Models. How Ignorable is Missing at Random?. The Expectation-Maximization Algorithm. Design Considerations. Case Studies.