Course catalogue doctoral education - HT19

  • Application can be done between 2019-04-15 and 2019-05-15
Application closed
Title Biostatistics II: Logistic regression for epidemiologists
Course number 1513
Programme Epidemiology
Language English
Credits 1.5
Notes The course meets the requirements for a general science course.

Date 2014-04-03 -- 2014-04-15
Responsible KI department Department of Medical Epidemiology and Biostatistics
Specific entry requirements Knowledge in epidemiology and biostatistics equivalent to "Epidemiology I: Introduction to epidemiology" and "Biostatistics I: Introduction for epidemiologists" or corresponding courses.
Intended learning outcomes After successfully completing this course you as a student are expected to be able to:
- choose a suitable regression model for assessing a specific research hypothesis using data collected from an epidemiological study, fit the model using standard statistical software, evaluate the fit of the model, and interpret the results.
- explain the concept of confounding in epidemiological studies and demonstrate how to controll/adjust for confounding using statistical models.
- apply and interpret appropriate statistical models for studying effect modification.
- critically evaluate the methodological aspects (design and analysis) of a scientific article reporting an epidemiological study.

Learning outcomes are classified according to Bloom´s taxonomy: knowledge, comprehension, application, analysis, synthesis, and evaluation.
Contents of the course This course focuses on the application of logistic regression in the analysis of epidemiological studies. Topics covered include a brief introduction to categorical data analysis, simple logistic regression, interpretation of parameters for continuous and categorical predictors, multivariate logistic regression, confounding and interaction, model fitting and model diagnostics, conditional logistic regression. Multinomial and ordinal logistic regression will be outlined.
Teaching and learning activities Lectures, computer lab with exercises focusing on analysis of real data sets using statistical software, exercises not requiring statistical software, group discussions, literature review.
Compulsory elements Only the examination is compulsory.
Examination To pass the course, the student has to show that the learning outcomes have been achieved. The course grade is based solely on a written examination. The focus of the exam will be on understanding concepts and their application to analysis of epidemiological studies rather than mathematical detail. The course examination will be held within one week of the final day of the course. 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 Compulsory texts Eric Vittinghoff Stephen C. Shiboski David V. Glidden Charles E. McCulloch. Regression Methods in Biostatistics. Springer; 2004. Jewell, Nicholas P, Statistics for Epidemiology Texts in Statistical Science, CRC Press, 2004 Recommended texts Dupont WD. Statistical Modeling for Biomedical Researchers. Cambridge University Press; 2007.
Number of students 12 - 25
Selection of students Eligible doctoral students will be prioritized according to 1) the relevance of the course syllabus for the applicant's doctoral project (according to written motivation), 2) date for registration as a doctoral student (priority given to earlier registration date). To be considered, submit a completed application form. Give all information requested, including a short description of current research and motivation for attending, as well as an account of previous courses taken.
More information Course dates are: April 3, 4, 7, 8 and 10. Examination on April 15. The course is extended over 2 weeks (but still 5 full course days) in order to promote reflection and reinforce learning. Prerequisite knowledge in epidemiology and biostatistics equivalent to "Epidemiology I: Introduction to epidemiology" (1577) and "Biostatistics I: Introduction for epidemiologists" (1579) or corresponding courses. Prior knowledge in Stata software is strongly recommended.
Additional course leader
Earlier evaluation of the course Evaluation report
Course responsible Rino Bellocco
Department of Medical Epidemiology and Biostatistics


Contact person Gunilla Nilsson Roos
Institutionen för medicinsk epidemiologi och biostatistik
08-524 822 93