30226
Advanced seminar
WiSe 21/22: Intermediate Regression Analysis
Jan Paul Heisig
Information for students
ACHTUNG! Diese LV wird in Präsenz durchgeführt, siehe Raumangaben.
CAUTION! This course will take place in presence. Check the location info.
CAUTION! This course will take place in presence. Check the location info.
Comments
This course is directed at students who already have a background in
linear regression and inferential statistics. We will begin with a brief
recap of conventional linear regression and discuss some issues that are
of great importance in applied research but often receive only limited
attention in introductory courses (e.g., the interpretation and
visualization of interaction effects). The main part of the course will
focus on generalized linear models for categorical outcomes and count
data, including binary, ordered, and multinomial logistic as well as
Poisson regression. Topics covered in the course include:
- the linear probability model and its limitations;
- the basic logic of logistic regression and other generalized linear models;
- prediction and interpretation (including average marginal/partial effects and marginal/partial effects at the mean);
- fundamentals of maximum likelihood estimation;
- model selection and goodness of fit; model diagnostics;
- (non-)comparability of coefficients across models and groups (optional).
16 Class schedule
Regular appointments
Wed, 2021-10-20 10:00 - 12:00
Wed, 2021-10-27 10:00 - 12:00
Wed, 2021-11-03 10:00 - 12:00
Wed, 2021-11-10 10:00 - 12:00
Wed, 2021-11-17 10:00 - 12:00
Wed, 2021-11-24 10:00 - 12:00
Wed, 2021-12-01 10:00 - 12:00
Wed, 2021-12-08 08:00 - 12:00
Wed, 2021-12-15 08:00 - 12:00
Wed, 2022-01-05 10:00 - 12:00
Wed, 2022-01-12 10:00 - 12:00
Wed, 2022-01-19 10:00 - 12:00
Wed, 2022-01-26 10:00 - 12:00
Wed, 2022-02-02 10:00 - 12:00
Wed, 2022-02-09 10:00 - 12:00
Wed, 2022-02-16 10:00 - 12:00