Longitudinal Data Analysis Using Discrete and Continuous Responses
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Longitudinal Data Analysis Using Discrete and Continuous Responses
Duration: 21 hours
This course is for scientists and analysts who want to analyze observational data collected over time. It is not for SAS users who have collected data in a complicated experimental design. They should take the Mixed Models Analyses Using the SAS System course instead.

The self-study e-learning includes:

  • Annotatable course notes in PDF format.
  • Virtual lab time to practice.
Learn How To
  • Create individual and group profile plots and sample variograms.
  • Use the MIXED procedure to fit a general linear mixed model and a random coefficient model.
  • Plot information criteria for models with selected covariance structures.
  • Generate diagnostic plots in PROC MIXED.
  • Fit a binary generalized linear mixed model in the GLIMMIX procedure.
  • Fit an ordinal generalized linear mixed model and a model with spline effects in PROC GLIMMIX.
  • Fit a binary GEE model in the GENMOD procedure.
  • Who Should Attend
    Epidemiologists, social scientists, physical scientists, and business analysts
    Prerequisites
    Before attending this course, you should be able to:;
  • Execute SAS programs and create SAS data sets.
  • Fit models using the GLM and REG procedures in SAS/STAT software. ;You can gain the programming experience by completing the SAS Programming 2: Data Manipulation Techniques course. You should also be familiar with the MIXED procedure. You can gain this experience by completing the Statistics 2: ANOVA and Regression course.
  • SAS Products Covered
    SAS/STAT;SAS/GRAPH
    Course Outline
    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.
  • THIS COURSE IS PART OF

    SAS Social and Behavioral Research​ Learning Subscription



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