In this course an introduction to basic statistical methods useful for biomedical data analysis will be given. Concepts are taught in an intuitive manner, alternating between short lectures and practicals. This allows for plenty of interaction and illustration with examples of practical interest. Participants who aim to use more complex methods can use the concepts and skills learned during the course as basis, as the vast majority of statistical methods are implemented in R.
Program
• Exploratory data analysis
• Basic tests: t-test, Wilcoxon test; paired versions; ANOVA (F-test), Kruskal-Wallis
• Power and sample size determination
• Methods for count data: Tests for 2x2 tables and nx2 tables; Relative risk, odds ratio
• Regression models: Linear and logistic regression
• Logistic regression: also show the Analysis of Deviance table
• Survival data analysis
Prerequisites
Participants must be able to work with R and R packages to follow the course. Those with little or no experience in R must follow an introductory R course prior to following this course. Two suggestions are the Introduction to R course given by our group, and the “Using R for data analysis” course organized by the Boerhaave Nascholing given regularly at the LUMC.
In addition, it is strongly advised to learn to work with RStudio and RMarkdown. Those with no prior knowledge of RMarkdown can follow the tutorials here. During the course we will practice further, and the RMarkdown cheatsheets may be useful.
Participants must bring their own laptops capable of running R and RStudio. Please install R (from the Comprehensive R Archive Network-CRAN, for example from this mirror) and download and install RStudio before the course. Participants should also install the R package RMarkdown prior to the course.
Who should attend
Researchers who need to run their own statistical analyses, and want to do it in a transparent and reproducible manner. While most participants tend to be PhD students and postdocs, more senior researchers can also benefit from the course.
Course lecturers
Renee X. de Menezes
Renaud Tissier
Vincent Pappalardo
Terry Chan
Course duration
5 days, 09.00 - 16.30 hrs
Course costs
Free: NKI or AVL researchers
€ 250.00 (PhD Students)
€ 350.00 (other researchers, postdocs etc.)
€ 700.00 (Non-academic participants)
As we can accept a limited number of participants, we suggest those interested to register as soon as possible to guarantee a place.
NKI participants can register via the Learning Portal. Other participants should send an e-mail to secretariaat.psoe@nki.nl to register.
Note that registration for this course is independent of registration for other courses, such as “Introduction to R”. Participants with little work knowledge of R must therefore register for that course separately.
ECTs
Participants who have a minimum of 60% attendance and successfully complete the final assignment earn 1.5 ECTs.
No medical accreditation possible.
