4 papers
Why is Regularization Underused? An Empirical Study on Trust and Adoption of Statistical Methods
Konstantin Emil Thiel, Marléne Baumeister, Nicole Krämer +3
Statistical practice does not automatically follow methodological innovation. Regularization methods, widely advocated to reduce overfitting and stabilize inference, are readily av…
Multivariate and Multiple Contrast Testing in General Covariate-adjusted Factorial Designs
Marléne Baumeister, Konstantin Emil Thiel, Lynn Matits +3
Evaluating intervention effects on multiple outcomes is a central research goal in a wide range of quantitative sciences. It is thereby common to compare interventions among each o…
Early and Late Buzzards: Comparing Different Approaches for Quantile-based Multiple Testing in Heavy-Tailed Wildlife Research Data
Marléne Baumeister, Merle Munko, Kai-Philipp Gladow +3
In medical, ecological and psychological research, there is a need for methods to handle multiple testing, for example to consider group comparisons with more than two groups. Typi…
Quantile-based MANOVA: A new tool for inferring multivariate data in factorial designs
Marléne Baumeister, Marc Ditzhaus, Markus Pauly
Multivariate analysis-of-variance (MANOVA) is a well established tool to examine multivariate endpoints. While classical approaches depend on restrictive assumptions like normality…