Course weeks spring 2023
Probably some spots weeks 11-12
Course weeks autumn 2022
Weeks 46-47 in English given digitally in Zoom (double groups - 40 spots)
Weeks 48-49 in English - The course will be given in a classroom if possible depending on the Covid situation. If we have to change the format, we will post that information here and we will also give that information in the welcome letter for the course.
Note that 3 hp amounts to 2 weeks of fulltime study, both regarding credits and the actual extent, and that attendance is compulsory for all course days.
Pär-Ola Bendahl, email@example.com, Associate professor, Clinical sciences Lund, department of oncology and pathology (course 2 spring 2022 and course 1 autumn 2022)
Anton Nilsson, Anton.Nilsson@med.lu.se (course 1 and 3, spring 2022 and course 2 autumn 2022).
PhD-students at the Faculty of Medicine with a research project within clinical research. Passed course Applied statistics I is required together with basic knowledge in the statistical package used in the same course.
3 hp (two weeks long)
The course includes the following four blocks:
1. Design and analysis of studies with a focus on binary outcomes
• Cohort and case-control studies
• Incidence and risk measures
• Measures of association: Odds ratio, absolute and relative associations
• Basic survival problems (time-to-event)
2. Introduction to correlation- and regression analysis
• Spearman’s and Pearson’s correlation coefficients
• Simple linear regression
• Simple logistic regression
3. Regression analysis - advanced
• Introduction to Cox regression
• Multivariable modelling
4. Randomized Controlled Trials (RCT) and diagnostic studies
• Design and analysis of randomized controlled trials
• Diagnostic measures: sensitivity, specificity, predictive values
This course for clinical researchers focuses on regression methods, especially linear regression models for a continuous outcome variable and one or more independent variables: in what situations they can be used and how the results should be interpreted.
The course will also cover how regression methods can be used to assess and handle confounding and interaction. Further, other types of regression models such as for binary outcomes (logistic regression) and survival analysis (Cox regression) will be introduced. Additionally, statistical methods for diagnostic tests will be covered by introducing sensitivity, specificity, positive and negative predictive value, as well as choice of cut off with ROC-analysis. The course also introduces theory and regulations around randomized controlled trials.
Kirkwood B and Sterne J. Essential Medical Statistics. Blackwell Science, 2nd edition, 2003. Chapter: 10-16, 18-22, 26-27, 29, 34-38.
Available as e-book at Lund University Libraries (www.lub.lu.se)
The course will be held in English and requires active participation and access to laptop with installed statistical package that you are familiar with from earlier courses (SPSS, STATA or R). More information will be provided before the course.