Longitudinal Data Analysis with Discrete and Continuous Responses (LONG)

• execute SAS programs and create SAS data sets. You can gain this experience by completing the SAS Programming I: Essentials course.
• fit models using the GLM and REG procedures in SAS/STAT software. You can gain this experience by completing Statistics II: ANOVA and Regression course.

Longitudinal Data Analysis Concepts

• understanding the merits and analytical problems associated with longitudinal data analysis
• examining the differences between PROC GLM and PROC MIXED

Exploratory Data Analysis

• graphing individual and group profiles
• identifying cross-sectional and longitudinal patterns

General Linear Mixed Model

• understanding the concepts behind the linear mixed model
• examining the different covariance structures available in PROC MIXED
• fitting a general linear mixed model in PROC MIXED

Evaluating Covariance Structures

• creating a sample variogram that illustrates the error components in your model
• plotting information criteria for models with selected covariance structures

Model Development, Interpretation, and Assessment

• learning the model building strategies in PROC MIXED
• creating interaction plots
• specifying heterogeneity in the covariance structure
• computing predictions using EBLUPs
• fitting a random coefficient model in PROC MIXED
• generating model diagnostic statistics and plots in PROC MIXED

Longitudinal Models with Binary Responses

• examining the correlation structures available in PROC GENMOD
• fitting a binary GEE model in PROC GENMOD

Longitudinal Models with Ordinal Responses

• examining cumulative logit plots
• fitting an ordinal GEE model in PROC GENMOD

GEE Model Diagnostics

• generating diagnostic plots in PROC GENMOD
• computing GEE deletion diagnostic statistics in PROC GENMOD

Generalized Linear Mixed Models

• fitting a longitudinal model with a discrete response using the GLIMMIX procedure