Repeated Measures and Longitudinal Data (SL_113)
About Study Course
Objective
This course provides knowledge in the field of repeated measures which has become a necessary tool for analysing data involving e.g. random effects, correlated observations and missing data. The emphasis is on continuous longitudinal data and on how to use SAS and R to model and analyse repeated models. However, other types of repeated measures such as hierarchical models will also be discussed.
The purpose of this course is to provide idea and tools for mixed model methods. Such methods can be applied to a variety of situations involving correlated data such as in longitudinal data, clustered data, repeated measures and hierarchical analysis. Generalized models will also be touched upon briefly. The course aims to enable the participants to formulate a mixed model, define and interpret possible estimators, and implement a mixed model analysis for e.g. a repeated measures study.
Prerequisites
To follow this course, the student is required to be familiar with some basic mathematical and statistical concepts. Moreover, some computer skills are also required.
Learning outcomes
After the course acquisition students will know in-depth mixed models with emphasis on biomedical applications to process repeated measures and longitudinal data. This includes using SAS and R through practical sessions to analyse real life data.
The students will be able to:
• write and interpret mixed models for longitudinal data of different study designs.
• critically evaluate and interpret statistical inference for mixed models and longitudinal data.
• choose, apply, and interact with statistical software for mixed models.
After passing the course, the student will be competent to use the mixed model framework, to describe and analyse qualitatively common study designs and models with longitudinal data or otherwise correlated observations, conduct an appropriate statistical analysis of models covered in the course using software, the latest scientific knowledge, creative and innovative solutions for different target groups.
Study course planning
| Study programme | Study semester | Program level | Study course category | Lecturers | Schedule |
|---|---|---|---|---|---|
| Biostatistics, MFBS | 2 | Master’s | Required |
