4 citations · 14 across the 13 of their papers we have counts for
14 papers
Blinded sample size review for McNemar's test based on primary and surrogate endpoints
Markus Schepers, Werner Brannath, Esther Hoffmann +2
We develop blinded sample size re-estimation strategies for McNemar's test based on paired binary primary and secondary short-term surrogate endpoints. The development is motivated…
An exhaustive ADDIS principle for online FWER control
Lasse Fischer, Marta Bofill Roig, Werner Brannath
In this paper we consider online multiple testing with familywise error rate (FWER) control, where the probability of committing at least one type I error shall remain under contro…
The effect of estimating prevalences on the population-wise error rate
Remi Luschei, Werner Brannath
The population-wise error rate (PWER) is a type I error rate for clinical trials with multiple target populations. In such trials, a treatment is tested for its efficacy in each po…
Statistical optimization of expensive multi-response black-box functions
Andreas Mändle, Werner Brannath, Werner Wosniok
Assume that a set of process parameters , , determines the outcome of a set of descriptor variables , , via an unknown functional relati…
ADDIS-Graphs for online error control with application to platform trials
Lasse Fischer, Marta Bofill Roig, Werner Brannath
In contemporary research, online error control is often required, where an error criterion, such as familywise error rate (FWER) or false discovery rate (FDR), shall remain under c…
The Online Closure Principle
Lasse Fischer, Marta Bofill Roig, Werner Brannath
The closure principle is fundamental in multiple testing and has been used to derive many efficient procedures with familywise error rate control. However, it is often unsuitable f…
Simultaneous confidence intervals for an extended Koch-Röhmel design in three-arm non-inferiority trials
Martin Scharpenberg, Werner Brannath
Three-arm `gold-standard' non-inferiority trials are recommended for indications where only unstable reference treatments are available and the use of a placebo group can be justif…
Post-Selection Confidence Bounds for Prediction Performance
Pascal Rink, Werner Brannath
In machine learning, the selection of a promising model from a potentially large number of competing models and the assessment of its generalization performance are critical tasks…
Single-stage, three-arm, adaptive test strategies for non-inferiority trials with an unstable reference
Werner Brannath, Martin Scharpenberg, Sylvia Schmidt
For indications where only unstable reference treatments are available and use of placebo is ethically justified, three-arm `gold standard' designs with an experimental, reference…
A liberal type I error rate for studies in precision medicine
Werner Brannath, Charlie Hillner, Kornelius Rohmeyer
We introduce a new multiple type I error criterion for clinical trials with multiple populations. Such trials are of interest in precision medicine where the goal is to develop tre…
Is there a role for statistics in artificial intelligence?
Sarah Friedrich, Gerd Antes, Sigrid Behr +11
The research on and application of artificial intelligence (AI) has triggered a comprehensive scientific, economic, social and political discussion. Here we argue that statistics,…
Point and interval estimation of the target dose using weighted regression modelling
Saswati Saha, Werner Brannath
In a Phase II dose-finding study with a placebo control, a new drug with several dose levels is compared with a placebo to test for the effectiveness of the new drug. The main focu…
A multiple testing framework for diagnostic accuracy studies with co-primary endpoints
Max Westphal, Antonia Zapf, Werner Brannath
Major advances have been made regarding the utilization of artificial intelligence in health care. In particular, deep learning approaches have been successfully applied for automa…
Interpretation of Linear Regression Coefficients under Mean Model Miss-Specification
Werner Brannath, Martin Scharpenberg
Linear regression is a frequently used tool in statistics, however, its validity and interpretability relies on strong model assumptions. While robust estimates of the coefficients…