Applied Longitudinal Data Analysis, 7,5 credits

Course content

The course aims to provide specific and in-depth skills in the application of modern statistical analysis models for longitudinal data, with particular emphasis on random effects models (sometimes referred to as latent growth modelling, linear mixed models or multilevel analysis for repeated measurements), which are increasingly common in behavioural science research.

The course covers both basic and advanced methods of longitudinal data analysis. Particular focus will be placed on methods for handling missing data in repeated measurements of the same individuals over time. Model specification, parameter estimation and interpretation, statistical assumptions and model comparisons will also be covered in the course. Application takes the form of computer exercises, with a particular focus on training practical skills in using the Mplus and SPSS programmes to specify and evaluate data analysis models for longitudinal data.

Please contact the contact person in good time if you are interested in the course.

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Contact Hugo Hesser, hugo.hesser@oru.se.