Course weeks spring 2023
Course weeks autumn 2022
Weeks 35-36. Please note! The course will be given in Malmö instead, due to the building of Forum Medicum in Lund, that causes a lack of clssrooms at he moment.
Note - Compulsory attendance all day
Aleksandra Turkiewicz, Aleksandra.Turkiewicz@med.lu.se, PhD Statistician, Clinical Epidemiology Unit, Orthopaedics, Department of Clinical Sciences Lund, Lund University
Aldana Rosso - email@example.com
PhD-students at the medical faculty with a research project within biomedicine or laboratory medicine. Passed course in applied statistics I is required together with basic knowledge in the statistical package used in the same course.
Lecture rooms and/or Zoom.
Content of the course
The course includes four themes:
1) Non-parametric testing for the comparison of two or more groups
• Mann-Whitney test
• Wilcoxon Signed Rank test
• Kruskal-Wallis test
2) Introduction to regression and analysis of variance
• Simple linear regression
• Analysis of variance (ANOVA)
• Relation between t-tests, linear regression and ANOVA
• Multiple testing and its consequences
3) Issues in design of experiments
• Dependent and independent observations
• Randomization and blinding
• Statistical testing, power and confidence intervals
• Reporting of study design and statistical analyses in basic science papers
4) Reliability analyses
• Correlation versus agreement
• Limits of agreement
• Cohen's kappa for categorical data
This advanced course in applied statistics, specialising in biomedicine and laboratory medicine, provides the participant with an introduction to the necessary tools for designing and analysing experimental data in biomedicine and laboratory medicine. The course starts with non-parametric testing for group comparisons. The course also provides students with an introduction to regression and analysis of variance, as well as issues in design of experiments. Finally, the course addresses different types of reliability analyses..
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.