MEDICAL STATISTICS
Academic year and teacher
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- Versione italiana
- Academic year
- 2022/2023
- Teacher
- STEFANO OLGIATI
- Credits
- 6
- Didactic period
- Secondo Semestre
- SSD
- MED/01
Training objectives
- The program is based on practical examples; its aim is to develop a critical understanding of the Statistical Methods underlying Clinical Trials with an introduction into Artificial Intelligence Clinical trials. At the end of the course, the student will be able to design a clinical trial and interpret its results.
Prerequisites
- Suggested:
- Inglese livello B1
- Strumenti informatici in medicina Course programme
- 1) Introduction to clinical trials
2) Ethical issues
3) What is the question?
4) Study population
5) Basic study design
6) The randomization process
7) Blinding
8) Sample size
9) Baseline assessment
10) Recruitment of study participants
11) Data collection and quality control
12) Assessment and reporting of harm
13) Assessment of health-related quality of life
14) Participant adherence
15) Survival analysis
16) Monitoring committee structure and function
17) Statistical methods
18) Data analysis
19) Reporting and interpreting results
20) Regulatory Issues Didactic methods
- Lectures
Learning assessment procedures
- Written Examination with 66 multiple choice questions worth 0.5 points each.
> 60 correct answers = 30/30 cum laude
= 60 correct answers = 30/30
< 60 correct answers = 0.5 points x Number of Correct Answers
To pass the exam it is necessary to score 18 points.
The state of knowledge of the subject and the ability to apply critically the information acquired during the course will be evaluated. Reference texts
- Friedman, L.M., Furberg, C.D., DeMets, D.L., Reboussin, D.M. and Granger, C.B., 2015. Fundamentals of clinical trials. Springer.
