Reading and Writing Statistics in Clinical Publications
Weiterbildungskurs

This course familiarizes participants with the essential statistical principles clinical publications are commonly based on.

Participants disentangle the reported statistics in a number of high-ranking publications from both experimental and observational medical studies. By learning to understand the statistical principles that underlie these diverse publications, participants acquire the skills to critically evaluate a wide diversity of statistical results that they may encounter in the clinical literature.

At the same time, the gained statistical knowledge will aid participants to plan statistical analyses for their own future studies, to interpret the results of these analyses, and to present the statistical results in a way that is correct and convincing.

Aufbau / Form

This course requires participants to attend one afternoon session a week during 6 weeks. Each session typically consists of lectures and assignments, both performed individually and in groups.

Learning objectives
Upon successful completion of this course, participants will be able to

Understand the different levels of evidence. 
Formulate scientifically sound hypotheses.
Choose appropriate study designs.
Understand the importance of statistical analysis plans and selection of appropriate measurements.
Understand hypothesis testing, its specific techniques, and underlying assumptions.

Work load and credits
Approximately 60 hours of workload distributed over 6 weeks.
The crediting of 2 ECTS requires:

Completed pre-assignments.
Active participation in weekly discussions.
Completed homework assignments.

Note for PhD students:
The workload of this course will be transferred into ECTS credits automatically if the course is listed in your approved learning agreement.

Assessment format
To add this course to your academic record, please create a Learning Contract on MOnA, choosing:

your supervisor as the assessor
pass/fail as assessment

before the start day of the course and follow the instructions of your respective faculty.

Recommended reading
Will be announced in time before each session.

Zielpublikum / Teilnahmevoraussetzungen

PhD students of all PhD subject enrolled at the University of Basel, Faculty of Medicine.

Early career clinical researchers and other researchers from the University of Basel, Faculty of Medicine (Biomedical Engineering, Biomedical Ethics, Medicines Development, Nursing Science, Public Health/ Epidemiology or Sport Science) are eligible to register for the course.

Maximum 15 registered participants. Priority will be given to early career clinical researchers aiming for a habilitation.

Leitung

Dr. Andrea Kiemen

Lehrkörper

Marco Cattaneo, PhD, Senior Statistician, Department of Clinical Research
Gilles Dutilh, PhD, Senior Statistician, Department of Clinical Research
Nikki Rommers, PhD, Statistician, Department of Clinical Research

Kontakt

Mareike Gräter
Aus- und Weiterbildung
Departement Klinische Forschung (DKF), Universität Basel
c/o Universitätsspital Basel
Spitalstrasse 8/12
CH-4031 Basel

mareike.graeter@usb.ch
Tel. +41 61 556 59 76
Weiterbildungen Departement Klinische Forschung

Available Mon-Thu 08.30h - 13.30h

Kosten

Fee CHF 1'200
Reduced course fee DKF research group members (for details see *)

*) The Department of Clinical Research (DKF) offers training grants for members of DKF research groups which result in a reduced fee of CHF 600. Please note, that training grants can only be offered to DKF clinical research group members, who are working at the group leaders’ local study center.
Limited free places available for PhD Students of the Medical Faculty of the University of Basel or at Swiss TPH.

The reduction will be applied when registering for the program.

Cancellation and withdrawal
Cancellations made prior to the closing date for enrolment will not be subject to any charge. If a cancellation is made after the closing date for enrolment, the full applicable fee will be charged. Course fees already paid will not be refunded.