Medical Statistics with R - advanced class
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
- Survival data analysis
Dates & time, location 2027
- Wednesday June 16 - 09.00-17.00
- Thursday June 17 - 09.00-17.00
- Friday June 18 - 09.00-17.00
- Monday June 21 - 09.00-17.00
- Tuesday June 22 - 09.00-17.00
- Wednesday June 23 - 09.00-17.00
The course takes place in lecture room Zaal 4 (C.1.072). In the lecture room of the AVL, participants fully benefit from the interactive nature of the course. The course offers up to 35 places for NKI-AVL participants. This course is not available online.
Enrollment
You may only enroll when you participated in the Introduction to R course in the past or are very experienced in working with R.
Cancellation fee
This course has a waiting list. If for some reason you are unable to attend, please cancel your registration as soon as possible by email via avlacademie@nki.nl. If you don’t cancel on time (> 4 weeks), a fee will be deduced from your departments educational budget.
Preparations
Knowledge: Participants must have elementary knowledge of statistics, such as of quantities like mean, median and standard deviation. At the beginning we will review concepts needed shortly.
Laptop: 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. You will receive detailed instructions about how to prepare your laptop via email about 1 week prior to the course.
Costs
- Free - NKI-AVL or AvL researchers
- € 330.00 – PhD students (exclusive 21% BTW)
- € 440.00 – others from academia (Postdocs etc.) (exclusive 21% BTW)
- € 860.00 – others outside academia (exclusive 21% BTW)
Participants who have a minimum of 80% attendance and successfully complete the final assignment earn 2 ECTs.
Afterwards
- You will be able to write R scripts
- You will understand R scripts written by others
- You will be able to use R to perform statistical analyses of own data
- You will be able to generate analysis reports using RMarkdown
Language
English
Target audience
- PhD students, postdocs and researchers interested in learning more about R and running their own statistical analyses
- 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.
Contacts
Biostatistics Centre (biostatistics@nki.nl)
Remarks
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.