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Swedish title Introduktion till kvantil regression och relaterade metoder
English title Introduction to Quantile Regression and Related Methods
Course number 2833
Credits 1.5
Responsible KI department The institute of Environmental Medicine
Specific entry requirements Biostatistics I or corresponding knowledge.
Grading Passed /Not passed
Established by The Board of Doctoral Education
Established 2015-03-04
Purpose of the course
Intended learning outcomes The main objective of this course is to introduce regression techniques for analyzing data arising in epidemiology, environmental health, and other global health domains. After a brief review of regression methods, the course will focus on quantile estimation. Statistical reasoning will be emphasized through problem solving and applications. At the completion of this course, a student will be able to:
1) Interpret commonly used statistics and regression methods;
2) When reading journal articles, identify potential errors and limitations in the analyses;
3) Develop judgment about which statistical technique to use in a given situation; and
4) Implement the described statistical techniques, including estimation and hypothesis testing, using statistical software.
Contents of the course Course Topics:
The following is a tentative list of topics to be covered:
1. Descriptive statistics ¿ measures of location and dispersion; empirical quantiles
2. Advantages of using quantiles. Examples from the existing literature
3. The concept of regression. Examples of regression
4. Extending the concept of quantiles to a regression framework
5. Quantile regression: examples and applications to real datasets
6. Censored quantile regression: examples and applications to real datasets
Teaching and learning activities Laboratory Sessions: Lab sessions will take place every afternoon; they will be used to review the material that was covered in the lectures and to work through additional problems and computing issues. During these hands-on lab sessions, the students will have the opportunity to utilize the methods presented in the morning lectures to the analysis of real-life data examples.

Computing: This course will provide an introduction to the R statistical package. R is free software and can be downloaded at www.r-project.org. Full information about the usage of the software will be provided during the course. Any student who has his or her own favorite statistical package is welcome to use it. The final exam does not require the use of a computer.
Compulsory elements
Examination Final assignment that assesses that all learning outcomes of the course are reached.
Literature and other teaching material Fundamentals of Biostatistics, 7th Edition
Bernard Rosner; Duxbury Thomson Learning

Quantile regression,
Roger Koenker, Econometric Society Monographs
Course responsible Matteo Bottai
The institute of Environmental Medicine
08-524 870 24

matteo.bottai@ki.se
Contact person Johanna Bergman
The institute of Environmental Medicine


johanna.bergman@ki.se

Nobels väg 13

17177
Stockholm