Longitudinal Data Analysis Using Discrete and Continuous Responses

Course code: LONG42

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 SAS course instead.

The self-study e-learning includes:

  • Annotatable course notes in PDF format.
  • Virtual lab time to practice.
1 080 EUR

1 307 EUR including VAT

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Course dates

Starting date: Upon request

Type: E-learning

Course duration: 14 hours

Language: en

Price without VAT: 1 080 EUR


Starting date: Upon request

Type: Upon request

Course duration: 21 hours

Language: en

Price without VAT: 1 800 EUR


Type Course
Language Price without VAT
Upon request E-learning 14 hours en 1 080 EUR Register
Upon request Upon request 21 hours en 1 800 EUR Register
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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.


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.
  • Do you need advice or a tailor-made course?


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