Learning outcomes
The student will learn to understand how the clustered data arises from different kind of experimental settings and problem formulations. Basic analyses for the most common longitudinal, multilevel and latent class data with continuous- and categorical responses will be learned. The student will also learn to perform the analyses when data are missing as well as to use the appropriate statistical software for the analyses.
The extent of each topic varies according to the year of execution.
Contents
Normal mixed model and extensions, growth curve models, models for panel discrete (binary,count, categorical) observations, analysis of missing data, mixture or latent class regression, hierarchical and latent structure models.
Modes of study
- Degree Programme Students
- Other Students
- Open University Students
- Doctoral Students
- Exchange Students
To be announced in teaching schedule.
Evaluation
Numeric 1-5.Belongs to following study modules
2018–2019