Turnus of offer:
Course of studies, specific field and terms:
- Bachelor CLS 2016 (optional subject), mathematics, 5th or 6th semester
- Master CLS 2016 (optional subject), mathematics, 1st, 2nd, or 3rd semester
Classes and lectures:
- Generalized Linear Models (exercise, 1 SWS)
- Generalized Linear Models (lecture, 2 SWS)
- 35 Hours in-classroom work
- 15 Hours exam preparation
- 45 Hours programming
- 25 Hours private studies
- 30 Hours work on project
Contents of teaching:
- General overview of generalized linear models (GLM): - link and response function, - GLM algorithms: Newton-Raphson, Fisher Scoring, iterated weighted least squares, - convergence, - quality of the adaption, - residuals
- Continuous response models: Gaussian, log-normal, Gamma, log-Gamma for survival analysis, inverse Gaussian
- Dichotomous response models: logit, probit, cloglog
- Count data: Poisson, negative binomial with over- and underdispersion
- Ordinal response models: proportional odds model
- Disordered categorial response models: Multinomial logit and probit model
- Censored continuous response models: Tobit model
- The students are able to explain the theoretical bases of generalized linear models (GLM).
- They are able to explain areas of application for GLM.
- They are able to select a suitable GLM.
- They are able to estimate GLMs in R.
- They are able to explain the R source code in a presentation.
- They are able to judge the results of GLMs in R critically.
- They are able to evaluate algorithmic challenges of GLMs.
- They are able to explain conceptual problems of GLMs for categorial response variables.
- They are able to implement GLM in R.
- They are able to apply regression diagnostics to GLMs and to judge the results.
- They are able to describe the most important estimation algorithms for GLMs.
- They are able to list the statistical properties of GLMs.
Responsible for this module:
- Prof. Dr. med. Peter König
- Prof. Dr. rer. biol. hum. Inke König
- Agresti, Alan: Foundations of Linear and Generalized Linear Models - Wiley, 2015
- English, except in case of only German-speaking participants
Prüfungsvorleistungen können zu Beginn des Semesters festgelegt werden. Sind Vor- leistungen definiert, müssen diese vor der Erstprüfung erbracht und positiv bewertet worden sein.
Letzte Änderung: 27.9.2021