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

## Tools

### Apps

**interim analysis / error spending functions: simulator**

**effect size calculator for 2-way & repeated measures ANOVA**

^{run locally with runGitHub('effectSizes','ICDS-VubUZ')}

**didactical tool: effect size one-sided t-test**

^{run locally with runGitHub('shinyT','ICDS-VubUZ')}