About The Course
This Applied Logistic Regression course provides theoretical and practical training for epidemiologists, biostatisticians and professionals of related disciplines in statistical modeling with particular emphasis on logistic regression.
The increasingly popular logistic regression model has become the standard method for regression analysis of binary response data in the health sciences.
By the end of this course, students should
- Master methods of statistical modeling when the response variable is binary.
- Be confident users of the Stata package for computing binary logistic regression models.
This is a hands-on, applied course where students will become proficient at using computer software to analyze data drawn primarily from the fields of medicine, epidemiology and public health.
There will be many practical examples and homework exercises in this class to help you learn. If you fully apply yourself in this course and complete all of the homework, you will have the opportunity to master various methods of statistical modeling and you will become a more confident user of the Stata* package for computing linear, polynomial and multiple regression.
*Access to Stata will be provided at no cost for the duration of this course.
Note: Enrollment for this course will close on Wednesday, May 13, 2015.
This course was developed in partnership with the Centre Virchow-Villermé for Public Health Paris-Berlin, a bi-national centre of the Université Sorbonne Paris Cité and Charité – Universitätsmedizin Berlin. Special support was contributed from the Université Paris Descartes that also belongs to the community of Université Sorbonne Paris Cité.
Frequently Asked Questions
What resources will I need for this class?
The only resources you will need are time and determination to learn. We will provide you will all the course lecture notes, the computer software and the solutions to the homework assignments.
What is the most practical thing I'll learn if I take this class?
You'll learn how to build a statistical model that predicts a binary response variable from a subset of many potential predictors. Models like this are used extensively in scientific literature. This course will provide you with the skills necessary to understand and develop your own models.
Why should I bother with the homework assignments if the solutions are provided with them?
If you truly want to learn and be confident in your practical understanding of regression analysis, the key will be to work through the homework exercises. Using the solutions can help you through that process. Remember, the goal isn't to get the correct answer...but to learn and understand the process.
Students interested in this course should have background in introductory statistical methods. While not absolutely necessary, familiarity with some statistical software package (such as SPSS, SAS or R) would definitely be an advantage.
We will be making exclusive use of Stata for the course lectures and homework solutions. However, students who are proficient in other packages could use those packages in place of Stata.
Based on past experience we strongly encourage students to use Stata for this course as it will facilitate communications with the professor, the teaching assistants, as well as other students in the course.