Target group
Epidemiologists, social scientists, physical scientists, and business analysts
Course structure
Longitudinal Data Analysis Concepts
- Understanding the merits and analytical problems associated with longitudinal data analysis.
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 diagnostic plots in PROC MIXED using ODS Graphics.
Generalized Linear Mixed Models
- Fitting a binary generalized linear mixed model in PROC GLIMMIX.
Applications Using PROC GLIMMIX
- Fitting an ordinal generalized linear mixed model in PROC GLIMMIX.
- Fitting a generalized linear mixed model with splines in PROC GLIMMIX.
GEE Regression Models
- Fitting a binary GEE model in PROC GENMOD.
