- Docente: Simone Tiberi
- Credits: 6
- SSD: SECS-S/02
- Language: English
- Teaching Mode: Blended Learning
- Campus: Bologna
- Corso: First cycle degree programme (L) in Statistical Sciences (cod. 8873)
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from Feb 10, 2025 to Mar 18, 2025
Learning outcomes
By the end of the course the students know the basic concepts and the statistical methods for the analysis of problems in the biomedical sciences. In particular students should be able: -to calculate and interpret the principal epidemiological measurements in various types of epidemiological studies. -to fit and interpret generalized linear models applied to biomedical data. -to apply the methods and models for the analysis of survival data.
Course contents
- survival analysis (censoring, the Kaplan Meier estimator, parametric models, and the Cox proportional hazard model);
- study designs (cross sectional, case control, cohort, and clinical trial);
- modelling strategies (applications of logistic regression, ROC curve, multiple testing correction, and association versus causation);
- concepts of epidemiology and genetic epidemiology;
- modelling of transcriptomics data (basic idea of omics data, RNA-sequencing, differential gene expression, etc...).
Readings/Bibliography
Not mandatory.
1) D. G. Kleinbaum and M. Klein. Logistic Regression, 3nd
ed. Springer New York, 2010.
2) D. Collett. Modelling Survival Data in Medical Research, Chapman & Hall / CRC.
Teaching methods
Lectures, and lab sessions with R.
Lab sessions will be streamed live online (via Teams).
Assessment methods
Written exam, with multiple open questions about all topics covered.
Questions will also involve interpreting R scripts, similar to those used during the course.
The written exam may be replaced by an oral exam (of equal complexity) if 5 or fewer students register for an exam session.
Office hours
See the website of Simone Tiberi