Advanced Statistics in Epidemiology, 7.5 credits

A Bachelor’s degree or a professional qualification worth at least 180 credits in public health science, healthcare or other relevant social sciences subject area. English language skills equivalent to English B at Swedish upper secondary school.

The objective of this course is to  teach the students the biostatistics skills needed to perform statistical analysis of public health and epidemiologic data. The student will develop knowledge to choose, apply and interpret appropriate regression models to conduct his/her present and future research in public health epidemiology.

After successfully completing the course students should be able to:

• explain the main assumptions of linear regression models and in what scenarios they can be violated;
• propose, adjust, interpret, and perform diagnostic checks of linear regression models;
• explain the assumptions and uses of logistic and count data regression models and how these differ from linear regression models;
• propose, adjust, interpret, and perform diagnostic checks of logistic and count data regression models;
• appropriately specify, adjust, and interpret results of non-parametric and semi-parametric models for survival data;
• use SPSS software to carry out the above tasks.

The course covers linear regression, logistic regression, count data regression, generalised linear models, life tables and non-parametric and semi-parametric models for survival data. Among the topics covered are: hypothesis testing and confidence intervals for regression model parameters, maximum likelihood estimation and least squares criteria, model diagnostics, goodness of fit, collinearity and multicollinearity, fitted values, residuals.

The course is a mix of lectures and computing tutorials. In lectures, statistical concepts needed to understand regression models are introduced, illustrated, and discussed in class and group discussions. In computing tutorials, the statistical concepts are illustrated with examples from epidemiological studies and/or epidemiological data. Lectures and tutorials are alternating so as to give the student an opportunity to practice the methods taught in lectures in the computer laboratory. The software used is SPSS and once per week, STATA software exercises are introduced.

The acquired knowledge and skills will be examined through home examination, theoretical examination and practical examination.

Limited number of examinations or practical training sessions
Students who have not passed the regular examination are entitled to participate in five more examinations. If the student is not approved after four examinations, he/she is recommended to retake the course at the next regular course date, and may, after that, participate in two more examinations. If the student has failed six examinations/tests, no additional examination or new admission is provided.

The number of times that the student has participated in one and the same examination is regarded as an examination session. Submission of a blank examination is regarded as an examination. An examination for which the student registered but not participated in, will not be counted as an examination.

Examination will be provided during a time of two years after a possible cancellation of the course. Examination can take place according to an earlier literature list during a time of one year after the date when a major renewal of the literature list has been made.

Course evaluation will be carried out in accordance with the guidelines established by the Board of Education.

The course language will be English.