HNE-30806 Analytical Epidemiology

Course

Credits 6.00

Language of instruction:

English

Assumed knowledge on:

HNE-24806 Epidemiology and Public Health; MAT-24306 Advanced Statistics for Nutritionists; HNE-37306 Applied Data Analysis; HNE-31006 Study Design and Interpretation in Epidemiology and Public Health.

Continuation courses:

MSc Thesis Nutrition and Health over the Lifecourse or MSc Thesis Nutrition and Disease.

Contents:

In this advance course, students learn how to conduct and interpret data analysis in the framework of major epidemiogical designs. In addition, they will obtain basic skills and understanding of additional aspects of data-analysis relevant to the successful and efficient completion of their thesis in epidemiology.

Learning outcomes:

After successful completion of this course students are expected to be able to analyse data of cross-sectional longitudinal, case-control and cohort studies, i.e.:
- to execute and interpret descriptive statistics;
- to identify the need for, execution of, and interpretation of data analysis using linear regression models, logistic regression models, general and generalized linear models, mixed models, and Cox proportional hazard models;
- to identify the need for, execution of, and interpretation of meta-analysis;
- to identify the need for, execution of , and interpretation of stratified analysis;
- to identify the need for, execution of , and interpretation of effect modification;
- to identify the need for, execution of , and interpretation of analysis to control for confounding;
- to systematically organize and document data analysis, using the statistical program SAS;
- to design a protocol for data analysis and review that of others.

Activities:

Lectures, e-modules, literature study, and (individual) assignments.

Examination:

- computer based practical test with open questions (20%)
- written test with 3 or 4 structured open questions and 10 multiple choice questions (80%).
The practical test needs a minimum mark of 5.5 to pass.

Literature:

Course materials, e.g., literature (papers), assignments, handouts of the lectures, and announcements, will be made available via Blackboard.