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Lecturer : Raphaël Porcher (Université Paris Descartes)

Objective of the course

The course aims at introducing both concepts and methods used in clinical (or medical) research. It is integrated to the health science theme of the master program.The course will both emphasize the principles and concepts underlying the different goals of clinical research (prediction and causation) and develop on specific statistical methods that can be used to plan studies and analyze data in this context.

It will focus on notions and methods that are not covered by other courses of the master (e.g. design, survival analysis, causal inference), that will be tackled both from the theoretical and applied point-of-view.

Methods will be illustrated on several practical examples.


  • Design of clinical studies and trials
  • Principles of therapeutic evaluation, biases in clinical research (confounding bias, time-dependent bias)
  • Introduction to the analysis of censored data (aka survival or time-to-event data)
  • Principles of the validation of predictive models in health science
  • Introduction to causal inference


There are no formal prerequisites to this course, but undergraduate courses in probability or statistics will help.

Organization of courses

  • 7 lectures (3 hours), each comprising formal lectures and practical work
  • Final group home project presentation (3 hours)



  • Final exam (60%)
  • Home project and presentation (40%)