Modeling Syllabus

Instructor(s):
• Dr Vedaste Ndahindwa

Description of the course
Modeling will rely on information covered in Biostatistics I and Biostatistics II. The course provides a solid foundation in modeling including multiple linear regression, Multiple binary logistic regression, Poisson regression and survival analysis.
Courses will alternate between class sessions and practice sessions. Each class session will be three hours. Students should bring computers to class with Stata installed on the computers.

Learning objectives
By the end of the course, students will have improved understanding and skills to:
• Conduct multiple linear regression
• Conduct multiple logistic regression
• Conduct Poisson regression
• Compute survival analysis

References
• John P. Klein, Melvin L. Moeschberger. Survival Analysis: Techniques for Censored and Truncated Data. 2nd edition 2005. New York: Springer.
• David G. Kleinbaum, Mitchel Klein. Logistic Regression: A Self-Learning Text. 3rd edition 2010. New York: Springer.
• Michael H. Kutner, Christopher J. Nachtsheim, John Neter and William Li. Applied Linear Statistical Models. 5th edition 2005. Boston: McGraw-Hill International Edition.

Assessment Modalities
The grades will be based on the following:
• Assignments (for a total of 50% of grade).
• One in-class exam – 50% (CAT)
• Final exam (External exam)