General description

The course covers different types of regression models, i.e. linear regression, logistic regression, survival analysis, Poisson regression.

Learning outcomes

After completing the course the students can based on the research question select a suitable analysis method for the data. Students understand the details of the various types of multipredictor regression models, as well as their limitations. Students are able to properly use and understand the multipredictor models. Students can conduct the analysis using statistical software R and interpret the results of the analysis.

Contents

Simple linear regression, multiple linear regression, predictor selection, logistic regression and other models for binary responses, survival analysis (proportional hazards model and its extensions), Poisson regression, log-linear models, statistical computing with R

Teaching language

Evaluation

Belongs to following study modules

2015–2016

Teaching

Archived Teaching Schedule. Please refer to current Teaching Shedule.

DPIPEM04 Regression models