Linear and Logistic Regression Modelling in R
Learning Outcomes
The course is part of the Public Health Sciences Course Program. Together with Basic Statistics and Projects in R, Introduction to Epidemiology and Study Design, and Diagnostic Test Evaluation, the course covers central skills of the theme Core Methods in the Public Health Course Program.
At the end of this course, participants shall be able to:
- Understand the concept of regression and select the appropriate model type for a given outcome
- Build tailored regression models for their research questions
- Verify model assumptions, apply model diagnostic tools and select between competing models
- Program their regression analysis in R
- Correctly interpret regression output and results
Topics/Content
- The linear model and least squares estimation
- Model diagnostics for the linear model: residual analysis, assessing multiple collinearity, coefficient of determination (R2)
- Purposeful variable selection and model building, assessing linearity of association, confounding and effect modification, model selection criteria
- Maximum likelihood estimation, deviance, likelihood ratio tests, Wald tests
- Soft introduction to generalized linear models
- Models for dichotomous and categorical outcomes: logistic regression, conditional logistic regression, multinomial logistic regression, ordinal logistic regression
Activities / Program
- Lectures introducing concepts, theory and examples
- Computer labs with exercises in R.
Basic information
| Number | E046.217.25 |
|---|---|
| Dates | Tuesday 02.09.2025 |
| Times | 09:15-12:30 and 13:30-17:00 |
| Course location | Institute of Social and Preventive Medicine ISPM room 220, second floor Situation plan |
| Lead | PD Ben Spycher, Institute of Social and Preventive Medicine (ISPM), University of Bern |
| Seats max. | 24 people |
| Course language | English |
| Registration deadline | 19.08.2025 |
| Format | Individual event from Public Health Sciences Course Program You will receive a certificate of attendance. |
| Governing Unit |
Faculty of Medicine, University of Bern |
| ECTS info |
1.5 ECTS point will be credited for this course For an accreditation of the ECTS, a minimum of 80% attendance and active participation incl. completion of assignments and assessments are required. root number KSL: 484096
|
Target audience
All PhD students, Post-docs, clinicians, and public health practitioners that are interested in applying regression models in their research.
Special
This course builds on the material covered in the courses ‘Basic Statistics and Projects in R’ and ‘Introduction to Epidemiology and Study Design’. Students should bring their own laptops with installed, recent versions of R and RStudio.
The course is offered once a year.
Application and admission procedure
A tertiary education degree is required. The program manager decides on the final admission. Priority is given to PhD students.
Application process: You are requested to enroll online. Seats will be allocated according to date of enrolment. Three weeks before the course/workshop at the latest, the administration will decide and inform about running or cancelling the course/workshop.
Costs
Amount still open
Administrative / Payment modalities
Registration fees are waived for PhD students of the University of Bern who commit to the whole course attendance. To avoid being invoiced, it is mandatory that you indicate your institute and the matriculation number upon registration for the course. Please note cancellation regulations below.
Course fees for other participant categories:
PostDocs Uni Bern CHF 150
Other participants Uni Bern CHF 450
Participants other academic institutions 900
Other participants CHF 1260
Participants completing the entire PHS Course Program benefit from a reduction; overview course fees here.
Cancellation regulations
After the closing date for registrations, the organisers will decide whether the course can take place. The decision is based on the number of registrations.
Contact
University of Bern
Public Health Sciences Course Program
c/o Institute of Social and Preventive Medicine (ISPM)
Mittelstrasse 43
3012 Bern
Switzerland
Tel: +41 31 684 34 04