11 citations · 11 across the 1 of their papers we have counts for
5 papers
Netboost: Boosting-supported network analysis improves high-dimensional omics prediction in acute myeloid leukemia and Huntington's disease
Pascal Schlosser, Jochen Knaus, Maximilian Schmutz +7
Background: State-of-the art selection methods fail to identify weak but cumulative effects of features found in many high-dimensional omics datasets. Nevertheless, these features…
The population-attributable fraction for time-dependent exposures and competing risks - A discussion on estimands
Maja von Cube, Martin Schumacher, Sebastien Bailly +5
The population-attributable fraction (PAF) quantifies the public health impact of a harmful exposure. Despite being a measure of significant importance an estimand accommodating co…
The population-attributable fraction for time-dependent exposures using dynamic prediction and landmarking
Maja von Cube, Martin Schumacher, Hein Putter +3
The public health impact of a harmful exposure can be quantified by the population-attributable fraction (PAF). The PAF describes the attributable risk due to an exposure and is of…
Causal inference with multi-state models - estimands and estimators of the population-attributable fraction
Maja von Cube, Martin Schumacher, Martin Wolkewitz
The population-attributable fraction (PAF) is a popular epidemiological measure for the burden of a harmful exposure within a population. It is often interpreted causally as propor…
A coordinate-wise optimization algorithm for the Fused Lasso
Holger Höfling, Harald Binder, Martin Schumacher
L1 -penalized regression methods such as the Lasso (Tibshirani 1996) that achieve both variable selection and shrinkage have been very popular. An extension of this method is the F…