Advanced Statistics

URL study guide

https://studiegids.vu.nl/en/courses/2024-2025/AM_470826

Course Objective

Background: students from the Master Health Sciences continue to have a wide variety of professional careers in
- and outside of academia. Handling and interpretation of data will play an important role in many of these settings. This course provides a first introduction to advanced topics in data analysis that are likely to be encountered when working in the field of health sciences. After this course, you will understand the basic principles of working with clustered data, longitudinal data, and time components in your data. You will be able to apply theoretical concepts to actual data analysis. Furthermore, you can present data analysis results in an engaging and concise manner, and geared towards to your relevant audience. The premise for all this work is that your primary research question drives your methodological and analytical choices, an important concept that will be reinforced during the course. Intended learning outcomes: After completing this course you should be able to
- explain and apply the basic principles analyzing clustered data
- explain and apply the basic principles analyzing longitudinal data
- choose and apply appropriate methods for accounting for time in your analysis
- present findings from a data analysis assignment around any of the above topics
- reflect on choices in data analysis approaches in the field of health sciences

Course Content

This course provides a first introduction to advanced topics in data analysis that you will likely encounter when working in the field of health sciences. We will explore the identification and handling of clustered data that challenge the assumptions of standard statistical techniques. We will also focus on the analysis of longitudinal data that are seen frequently in the field of health sciences, and especially how we can account for time in the analysis. Although the course expands knowledge of, and hands-on experience in analytical techniques, it has not the aim to make you an expert in these topics. This course does provide you with the confidence to engage in discussions surrounding complex analytical approaches in the field of health sciences.

Teaching Methods

Lectures: approximately 24 hours Work groups: approximately 24 hours Individual assignment: approximately 24 hours Preparation and self-study.

Method of Assessment

Written exam (70%) Data analysis assignment (30%) Presentation of individual assignment (pass / fail) You should have at least a 5.5 for the each of the written exam and the data analysis assignment, and a “pass” for the presentation in order to complete the course successfully.

Literature

- lecture notes
- applicable literature provided during the course Recommended textbooks:
- Twisk JWR. Applied longitudinal data analysis for epidemiology. A practical guide. Cambridge University Press, Cambridge, UK, 2003.
- Twisk JWR. Applied multilevel analysis. A practical guide. Cambridge University Press, Cambridge, UK, 2006

Target Audience

This course is aimed at students from the Master Health Sciences.

Entry Requirements

You must have adequate knowledge of epidemiology and standard analytical techniques including regression.