Course catalogue doctoral education - VT20

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Title Biostatistics II: Logistic Regression for Epidemiologists
Course number 3043
Programme Epidemiologi
Language English
Credits 2.0
Notes The course meets the requirements for a general science course.

Date 2020-01-27 -- 2020-02-04
Responsible KI department Institutionen för medicinsk epidemiologi och biostatistik
Specific entry requirements Knowledge in epidemiology and biostatistics equivalent to ""Epidemiology I: Introduction to epidemiology"" and ""Biostatistics I: Introduction for epidemiologists"" or corresponding courses
Purpose of the course The aim is to introduce statistical methods for categorical outcome data.
Intended learning outcomes After successfully completing this course you as a student are expected to be able to:
- estimate and explain the difference between absolute and relative effect measures, including but not limited to odds ratio, risk ratio, and risk difference,
- perform tests for multiple category outcome data,
- fit and interpret the results of the logistic regression model,
- apply and interpret appropriate statistical models for studying effect modification and confounding.
- critically evaluate the methodological aspects (design and analysis) of a scientific article reporting an epidemiological study.
Contents of the course This course focuses on the application of methods for binary data and in particular logistic regression in the analysis of epidemiological studies. Topics covered include a brief introduction two-by-two tables and methods for estimating relative effect measures. Then moving on to univariable and multivariable models for binary outcomes to estimate relative and absolute effect measures, with the interpretation of parameters categorical predictors, flexible modeling of quantitative predictors, confounding and interaction, model fitting and model diagnostics.
Teaching and learning activities Lectures, exercises focusing on analysis of real data using statistical softwares, exercises not requiring statistical software, group discussions, literature review.
Compulsory elements
Examination To pass the course, the student has to show that the intended learning outcomes have been achieved. The course grade is based on the individual written examination (summative assessment). Students who do not obtain a passing grade in the first examination will be offered a second examination within two months of the final day of the course. Students who do not obtain a passing grade at the first two examinations will be given top priority for admission the next time the course is offered. If the course is not offered during the following two academic terms, then a third examination will be scheduled within 12 months of the final day of the course.
Literature and other teaching material Suggested reading:
Hosmer DW, Lemeshow S, and Sturdivant, RX. Applied Logistic Regression, 3rd Ed, A Wiley-Interscience Publication, John Wiley & Sons Inc., New York, NY, 2013.

Jewell NP. Statistics for Epidemiology, Chapman & Hall, New York, 2003.

Number of students 8 - 25
Selection of students Applicants will be prioritized according to 1) the relevance of the course syllabus for the applicant’s doctoral project (according to written information), 2) date for registration as a doctoral student (priority given to earlier registration date). Submit a completed application form. Give a short description of current research training and motivation for attending, as well as an account of previous courses taken. Prior knowledge of statistical programmes R or Stata is recommended.
More information The course is extended over time in order to promote reflection and reinforce learning. The course will be held the dates January 27, 28, 30, 31 and February 3, 4.
Additional course leader
Latest course evaluation Course evaluation report
Course responsible Rino Bellocco
Institutionen för medicinsk epidemiologi och biostatistik

Rino.Bellocco@ki.se

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Contact person Gunilla Nilsson Roos
Institutionen för medicinsk epidemiologi och biostatistik
08-524 822 93
gunilla.nilsson.roos@ki.se