Syllabus database for doctoral courses
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Syllabus database for doctoral courses
SYLLABI FOR DOCTORAL COURSES
Swedish title | Introduktion till kvantil regression och relaterade metoder |
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English title | Introduction to Quantile Regression and Related Methods |
Course number | 2833 |
Credits | 1.5 |
Responsible KI department | Institutet för miljömedicin |
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 Institutet för miljömedicin 08-524 870 24 matteo.bottai@ki.se |
Contact person |
Johanna Bergman Institutet för miljömedicin johanna.bergman@ki.se Nobels väg 13 17177 Stockholm |