Missing data, particularly in longitudinal studies

Aim

Analysis of longitudinal data is essential in many projects in medical research, be it clinical, experimental or epidemiological. Missing data are unavoidable in most
contexts, and adequate data analysis requires correct classification and handling of these. As a result of the course, participants should be able to perform a basic analysis for a particular longitudinal data set at hand, using linear, generalized linear, and non-linear tools for longitudinal data. Based on a selection of exploratory tools, the nature of the data, and the research questions to be answered in the analyses, they should be able to construct and appropriate statistical model, to fit the model within the SAS framework, and to interpret the
obtained results. Further, participants should be aware not only of the possibilities and strengths of a particular selected approach, but also of its drawbacks in comparison to other methods. The course will be explanatory rather than mathematically rigorous.

Location & Organization

Organizer

DGSB - Danish Graduate School in Biostatistics

Course Director

Niels Keiding

Location / venue

University of Copenhagen (Faculty of Health Sciences)

Timing & Workload

Duration 2 days
ECTS points 2
Frequency Every third year
 

Examination yes

Criteria

Is the course taught in English? yes
Is documentation available? (book, syllabus)? yes
Is the course open for external researchers? yes

More Information

http://www.phdbiostat.dk/biostatistik_en/kurser/