Navigation auf


Department of Psychology Psychological Methods, Evaluation and Statistics

Shiny-App Collection

On this page you can find a collection of Shiny apps, that were created by team members, students and interns.

App Information Author
Tree depth Varimp german Influence of tree depth on variable importance in random forests Andrea Schaffert
Transformations Varimp german Influence of transformations on Variable Importance in random forests Nadine Galsterer
Regression Assumptions german Assumptions of the linear regression model Martin Sterchi
Interaction Importance german Detecting interactions in random forests Sven Theiler
Regression german Illustration of the normality assumption for the errors Martin Sterchi
Random Forests english Variable Selection Bias and Prediction Accuracy in randomForest and cforest Krenar Sherifi
Anchor Point Selection english Illustration of the method from this article Lucas Kohler

SampleSizeR english

Sample size planning for completely randomized design

Bernadetta Tarigan, Reinhard Furrer and Kalina Cherneva

Positive Predictive Values english


Sascha Sauer
Multilevel models german   Noah Bosshart
Poisson regression german   Chung Man (Mandy) Fong
Duckling app german Optional Stopping (for the Scientifica exhibition 2019), instruction (PDF, 340 KB), background (PDF, 2 MB) Noah Bosshart
Power and sample size german | english   Lennart Schneider