Koen Derks's repositories
rcityviews
rcityviews is a user-friendly R interface for creating stylized city maps using OpenStreetMap (www.openstreetmap.org) data, implemented as an R package and a Shiny web application.
digitTests
digitTests is an R package providing statistical tests for detecting irregular digit patterns. The package is also implemented with a graphical user interface in the Audit module of JASP (www.jasp-stats.org), a free and open-source statistical software program.
OptimalForaging
A R Shiny application to simulate optimal foraging models and test such models on yourself.
BayesianNormalityCheck
An application to perform Bayesian normality checks based on my master thesis.
cheatsheets
RStudio Cheat Sheets
CirrusMaximus
Cirrus Maximus is an extension for your web browser that enables scraping and exporting data from the Cirrus online assessment platform.
jasp-desktop
JASP aims to be a complete statistical package for both Bayesian and Frequentist statistical methods, that is easy to use and familiar to users of SPSS
jaspAudit
The Audit module is developed to facilitate statistical auditing in both Bayesian and classical manifestations. The main feature is a workflow that helps guide auditors through the sampling process. Additionally, there are stand-alone analyses for planning, selecting, and evaluating a sample. The module is based on the R package jfa.
jaspMachineLearning
The Machine Learning Module
koenderks.github.io
Personal website, also hosted at https://koenderks.com.
LiteratureNetworksApp
This repository contains the code for an R Shiny app to estimate co-occurrence and citation network based on a literature search. The methodology is described in the paper Derks, K., Burger, J., van Doorn, J., Kossakowski, J. J., Matzke, D., Atticciati, L., ... & Cordesius, E. P. (2018). Network Models to Organize a Dispersed Literature: The Case of Misunderstanding Analysis of Covariance. Journal of European Psychology Students, 9(1).
ShinyNetworks
This Shiny R application serves the purpose of visualizing and comparing various free-scale and random growing graphs. Application made as part of the TquanT 2018 seminar on quantitative thinking.