Seminar Series: Statistics in Clinical Research
Course description
The course focuses on the most important statistical aspects and methods in clinical research. Through the course, participants will develop an understanding and critical evaluation of the statistical methods used in scientific publications. They will learn to develop a scientifically and statistically solid research question and analysis plan, and get an introduction to the correct use and interpretation of the most important statistical tools in clinical research.
Main topics covered during this course are: building a research question; study design; descriptive statistics; hypothesis testing, p-values and confidence intervals; diagnostic measures; linear and logistic regression; survival analysis; writing a statistical analysis plan.
Students will also get the opportunity to bring and discuss own cases and topics.
Course structure
This 9-week course requires students to attend a 1.5-hour session per week (1-hour session on the specific topic of the week + 0.5-hour of discussion).
Recommended reading
Will be announced in due time per session.
Course dates
Tuesdays, 15.30 - 17.00h
Session 1 (October 22, 2024) | The scientific method and building a research question |
Session 2 (October 29, 2024) | Descriptive statistics, data presentation and visualisation |
Session 3 (November 5, 2024) | P-values and confidence intervals |
Session 4 (November 12, 2024) | Diagnostic measures |
Session 5 (November 19, 2024) | Linear (multiple) regression |
Session 6 (November 26, 2024) | Logistic regression |
Session 7 (December 3, 2024) | Time-to-event/Survival analysis |
Session 8 (December 10, 2024) | Writing a statistical analysis plan |
Session 9 (December 17, 2024) | Bring your own research! |
Please note that the detailed course progamme is subject to change.
Attending single sessions is possible if the course is not fully booked.
For information on free seats please contact Michael Coslovsky after the expiration of the registration deadline.
Location
Sitzungszimmer, Spitalstr. 8, EG right (raised ground floor), 4056 Basel
Target audience/prerequisites for attending
Doctoral students in Medicine and PhD students of the PhD subject Clinical Research enrolled at the University of Basel, Faculty of Medicine. Moreover, PhD students of the other PhD subjects of the Faculty of Medicine (Biomedical Engineering, Biomedical Ethics, Medicines Development, Nursing Science, Public Health/ Epidemiology or Sport Science) are eligible to register for the course. If the course should not be fully booked, we are happy to welcome all other persons interested.
Minimum 8 and maximum 20 registered participants.
Learning objectives:
Upon successful completion of this course, the students will able to
- Understand the principals of the scientific method
- Develop a scientifically and statistically solid research question
- Critically evaluate statistical methods used in scientific publications
- Choose the correct analysis approach for their research question and write a detailed analysis plan
- Assess available resources offered by the DKF for their research projects
Work load and credits
Maximum of 15 hours of work load distributed over 9 weeks. Attendance to all but two sessions is required for acquiring a certificate of attendance.
Note for PhD students: The workload of this course will be tranfered into ECTS credits automatically if the course is listed in your approved learning agreement.
Assessment format
None
Study direction
Michael Coslovsky, PhD
Teamleader Data Analysis/Statistics, Department of Clinical Research
Teaching staff
Michael Coslovsky, PhD
Marco Cattaneo, PhD, Senior Statistician, Department of Clinical Research
Nikki Rommers, PhD, Statistician, Department of Clinical Research
Deborah Vogt, PhD, Senior Statistician, Department of Clinical Research
Contact
Mareike Gräter
Training and Education, Department of Clinical Research
Costs
The course is free of charge.
Miscellaneous
Course language is English.
Certificate of attendance will be issued after successful course completion (at least 7 sessions out of 9).
There will be no option to participate in the course online.
Registration
If you are interested in the course, please register here.