resources

Workshops

= FLAMES: Sample Size Calculation with exercise in GPower =   
Introduction of the necessary concepts (power, effect size and type I/II errors), with small exercises to promote statistical reasoning. After a focus on the comparison of 2 independent groups, several extensions are highlighted. [webpage]

= Sample Size Calculation with GPower =   
Introduction of the necessary concepts (power, effect size and type I/II errors), with small exercises to promote statistical reasoning. After a focus on the comparison of 2 independent groups, several extensions are highlighted. [webpage]

= Data Manipulation in R, tidyverse =   
Introduction of the tidyverse packages dplyr and friends for intuitive and flexible data management in R. [webpage]

= Visualization in R, tidyverse =   
Introduction of the tidyverse package ggplot2 for intuitive and flexible visualization in R.  [webpage]

Presentations

= R Primer =   
Quick introduction to R, to get started and as a preperation for the workshops Data Manipulation and Visualization in R. [webpage]

= Data Representation =   
Brief introduction to help structure data in preparation of statistical analyses; highlighting errors, inconveniences, common problems and solutions, part of 'about R'. [webpage]

= Methodological & Statistical issues in research proposals =   
Info session for experienced researchers to help highlight relevant aspects of the research aim and design that are part of a research proposal. [webpage] [pdf]

= A first prep step into tidyverse =   
Ultra brief introduction on some starting issues when starting to use tidyverse in R [webpage]

= Programming and R, a few basic hints =   
Brief introduction on the key issues related to programming, to get started with programming in R [webpage]

Technical Notes

= Corona hospitalisation SIR model =   
Technical note on the analytical approximation of the popular SIR-equations which after reparametrization allow for straightforward parameter estimation and prediction of hospitalisation sustainability based on limited time series. Extensions that add flexibility are highlighted. [pdf] 

Please reference: Barbé, K.,  Blotwijk, S., & Cools, W. (2020) Data-driven epidemiological model to monitor the sustainability of hospital care, VUB Covid19 Technical Note No. ICDS043020.