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Instructors: Prof. Dr. Dirk Enzmann
Event type:
Seminar
Displayed in timetable as:
Profilseminar C6
Hours per week:
2
Credits:
6,0
Language of instruction:
German
Min. | Max. participants:
10 | 20
Comments/contents:
Topic of the course are "generalized linear models" (GLM), i.e. extensions of classic regression models with respect to the dependent (criterion) variable. Such regression models are useful tools of analysis in criminological research that encounters dichotomous dependent variables (such as measures of prevalence) or count variables (such as incidence or frequency measures). To this family belong procedures such as logistic regression models as well as models for count variables such as Poisson regression, negative binomial regression, and fractional logit and fractional count models.
Learning objectives:
- Understanding of the logic of generalized linear models;
- Ability to conduct respective analyses and to interprete results appropriately.
Didactic concept:
Lectures (online) and accompanying exercises using a computer; additional offer: Introduction to Stata (Friday 9:15-10:00) using the same Zoom-link
Literature:
- Acock, A. C. (2018). A Gentle Introduction to Stata. College Station, TX (6th Ed.): Stata Press.
- Fox, J. (2016). Applied Regression Analysis & Generalized Linear Models. Los Angeles, CA: Sage.
- Hardin, J. W. & Hilbe, J. M. (2012). Generalized Linear Models and Extensions. College Station, TX: Stata Press.
Additional material will be made available via UHHShare.
Additional examination information:
Additional examination information:
Weekly assignments: Readings and computer exercises;
Academic assessment: Proof of attendance (requires weekly assignments)
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