Logistic Regression in R
Synopsis
Logistic regression for studying associations between binary outcomes and possible explanatory factors will be explained. The focus of the course will be on practical application and interpretation rather than theory. Practical sessions will be with R under the free and open source integrated development environment RStudio.
Target audience
Scientists and technologists who already have some knowledge of basic statistics but whose it is lacking in the area of regression methods for binary response data.
Topics
- Motivation examples of binary data (ungrouped and grouped data)
- Logistic regression model description (link function, mean, variance)
- Model interpretation: computing the odds ratio
- Hypothesis testing and confidence intervals
- Model comparisons and selection strategies
- Dealing with confounding and interaction
- Measure of model adequacy: goodness-of-fit tests and residuals
Schedule
This is a three-days course with the following structure:
- 15:00 - 18:00 Lecture (computer lab)
Lecturer
Valeska Andreozzi, Researcher at the Center of Statistics and Applications of University of Lisbon
Registration
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