Course: Statistical Modelling in Biomedicine

Course type: elective
Lecturer: Lara Lusa, Ph.D., Associate Professor
 

Study programme and level Study field Academic year Semester
Applied statistics, second level All modules 1st or 2nd 1st or 2nd

For the timeline see Curriculum.

Prerequisites:

  • Valid inscription to start the course, positively evaluated home work for taking the exam.

Content (Syllabus outline):
General concepts:

  • Formulation of models, estimation of parameters, interpretation
  • Interaction, relaxing the linearity assumption
  • Explained variation
  • Overfitting
  • Resampling, validation of models
  • Using R in statistical modelling

Logistic regression:

  • Fitting the model: maximum likelihood, point and interval estimation of the odds ratio, test statistic, residuals, goodness of fit, influential points
  • Interpretation of the model
  • Evaluating predictive value of the model
  • ROC curves

Objectives and competences:
The aim is for students to learn about strategies of statistical modelling, and to evaluate and validate a model, using logistic regression as an example.

Intended learning outcomes:
Students will be able to fit and interpret models, which will adequately fit the data.

 

Contact

Main contact:
e-mail: info.stat (at) uni-lj.si

Contact for administrative questions (enrolment, technical questions):
Katarina Erjavec Drešar
University of Ljubljana, Faculty of electrical engineering, Tržaška cesta 25, 1000 Ljubljana.
room num.: AN012C-ŠTU
phone: 01 4768 209
e-mail: katarina.erjavec-dresar (at) fe.uni-lj.si