The course is intended primarily for the second year students of Master’s degree in statistics. The course is also suitable for students from other degree programmes such as Life Science Informatics and Data Science, exchange students and doctoral students of statistics and other disciplines who are interested in Real world evidence (RWE).
RWE is more and more commonly used to support decision making in several areas, particularly in health care. This course gives an introduction to what types of real world data are available, their benefits and weaknesses. Furthermore, the course gives introduction to potential pitfalls encountered in the RWE field, and statistical methods that are commonly applied.
Basic probability and statistics, regression models
Getting familiar to RWE, opportunities, pitfalls, and statistical methods. Able to develop a statistical analysis plan for a RWE study.
Recommended time/stage of studies for completion: 2nd year of master’s degree and doctoral studies
List relevant material covering the topics of
i) Real world data sources, opportunities and weaknessess
- ii) Research questions in RWE, statistical evidence (what can be answered)
ii) Study designs, causal infernce vs. associations
iv) Basic statistical methods, propensity scores
v) Study protocols, statistical analysis plans (written assingment)
- vi) Further topics in more advanced statistical methods
Attendance is compulsory, participation in group discussions after self-reading, and a writing assinmgent on statistical analysis plan.
Research articles and other (will be provided later)
Assessment practice: Between 1 to 5 (best)
Seminar course, self reading and writing assingments (18 h), group discussions (12 h), and a final written assingment.