Back to selection
| Semester | fall semester 2020 |
| Course frequency | Every fall sem. |
| Lecturers | Penelope Vounatsou (penelope.vounatsou@unibas.ch, Assessor) |
| Content | Generalised linear models Survival analysis Introduction to longitudinal data analysis Statistical inferences will be taught from the maximum likelihood approach. |
| Learning objectives | To understand, apply and interpret the results of statistical models for categorical and time to event independent data (logistic, poison, negative binomial, Cox proportional hazards and parametric survival regression models); to be able to identify the appropriate statistical model for data analysis, apply and interpret the results; to gain insight into statistical thinking; to apply the statistical software STATA for data analysis. |
| Comments | Methods: Lectures, exercises, computer practicals and project work |
| Admission requirements | advanced |
| Language of instruction | English |
| Use of digital media | No specific media used |
| Interval | Weekday | Time | Room |
|---|
No dates available. Please contact the lecturer.
| Modules |
Doctorate Science Epidemiology: Recommendations (PhD subject: Epidemiology) Module: Biostatistics and Computing (Master's Studies: Epidemiology) |
| Assessment format | continuous assessment |
| Assessment details | Written final exam & assignments |
| Assessment registration/deregistration | Reg.: course registration, dereg: cancel course registration |
| Repeat examination | no repeat examination |
| Scale | Pass / Fail |
| Repeated registration | as often as necessary |
| Responsible faculty | Faculty of Science, studiendekanat-philnat@unibas.ch |
| Offered by | Schweizerisches Tropen- und Public Health-Institut |