Biostatistik 2

Aim

The course aims to broaden and deepen the knowledge acquired in the compulsory PhD course in biostatistics. It is primarily intended for PhD students involved in clinical research projects, but may also be relevant to others.
A range of topics are covered, with an emphasis on understanding statistical concepts and methods. One week of full-time teaching is followed by two weeks of part-time work on an independent project

Learning outcomes

After completing the course, participants are expected to:

• have a basic understanding of the mathematical foundations of statistics
• be familiar with advanced statistical methods commonly used in clinical research, including survival analysis, propensity score methods, prediction models, methods for handling missing data, clustered data and ordinal outcomes, and methods for genetic data
• have a basic understanding of causality and the definition of treatment effects
• be able to critically discuss published clinical research results from a basic methodological perspective
• be familiar with the principles of statistical analyses in R

Course content

Maximum likelihood and bootstrap methods. Propensity scores. Methods for clustered data, ordinal outcomes and survival outcomes. Multiplicity. Prediction models. Treatment effects. Handling of missing data. Statistical genetics. Registry data. Agreement.

Teachers

Lars Lindhagen is the course director and teaches the course together with Albert Nilsson, Henrik Renlund, Inger Persson, Johan Lindbäck, Johan Westerbergh, Niclas Eriksson, Ollie Östlund and Tatevik Lakic.

More information about the course is available on the Uppsala University website