Publications (10)
Controlling false discoveries in high-dimensional situations: Boosting with stability selection
Benjamin Hofner, Luigi Boccuto, Markus Göker
Modern biotechnologies often result in high-dimensional data sets with much more variables than observations (n p). These data sets pose new challenges to statistical analysi…
gamboostLSS: An R Package for Model Building and Variable Selection in the GAMLSS Framework
Benjamin Hofner, Andreas Mayr, Matthias Schmid
Generalized additive models for location, scale and shape (GAMLSS) are a flexible class of regression models that allow to model multiple parameters of a distribution function, suc…
OpenML: An R Package to Connect to the Machine Learning Platform OpenML
Giuseppe Casalicchio, Jakob Bossek, Michel Lang +6
OpenML is an online machine learning platform where researchers can easily share data, machine learning tasks and experiments as well as organize them online to work and collaborat…
A Unified Framework of Constrained Regression
Benjamin Hofner, Thomas Kneib, Torsten Hothorn
Generalized additive models (GAMs) play an important role in modeling and understanding complex relationships in modern applied statistics. They allow for flexible, data-driven est…
Clinical trials with interim analyses: Standardizing Terminology to increase clarity
Elina Asikanius, Benjamin Hofner, Lisa V. Hampson +5
Interim analyses for group-sequential decision making are prevalent in clinical trials. Methodology is well established and has been routinely implemented over the last decades. St…
Stability selection for component-wise gradient boosting in multiple dimensions
Janek Thomas, Andreas Mayr, Bernd Bischl +3
We present a new algorithm for boosting generalized additive models for location, scale and shape (GAMLSS) that allows to incorporate stability selection, an increasingly popular w…
Biologists meet statisticians: A workshop for young scientists to foster interdisciplinary team work
Benjamin Hofner, Lea Vaas, John-Philip Lawo +3
Life science and statistics have necessarily become essential partners. The need to plan complex, structured experiments, involving elaborated designs, and the need to analyse data…
Platform Trials: the Impact of common Controls on Type One Error and Power
Quynh Nguyen, Katharina Hees, Benjamin Hofner
Platform trials offer a framework to study multiple interventions in a single trial with the opportunity of opening and closing arms. The use of a common control in platform trials…
An update on statistical boosting in biomedicine
Andreas Mayr, Benjamin Hofner, Elisabeth Waldmann +3
Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine-learning approach with classical statistical modelling, off…
Communicating results in trials with multiple hypotheses or adaptive design features
Elina Asikanius, Marcel Wolbers, Mouna Akacha +8
Over time, clinical trials have increasingly incorporated complex design and analysis elements such as interim analyses, adaptations, multiple endpoints, and sophisticated multipli…