170 citations · 433 across the 10 of their papers we have counts for
10 papers
Improving Software Engineering in Biostatistics: Challenges and Opportunities
Daniel Sabanés Bové, Heidi Seibold, Anne-Laure Boulesteix +9
Programming is ubiquitous in applied biostatistics; adopting software engineering skills will help biostatisticians do a better job. To explain this, we start by highlighting key c…
What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work?
Susanne Dandl, Torsten Hothorn, Heidi Seibold +3
Estimation of heterogeneous treatment effects (HTE) is of prime importance in many disciplines, ranging from personalized medicine to economics among many others. Random forests ha…
An Environment for Sustainable Research Software in Germany and Beyond: Current State, Open Challenges, and Call for Action
Hartwig Anzt, Felix Bach, Stephan Druskat +40
Research software has become a central asset in academic research. It optimizes existing and enables new research methods, implements and embeds research knowledge, and constitutes…
Open Science in Software Engineering
Daniel Méndez Fernández, Daniel Graziotin, Stefan Wagner +1
Open science describes the movement of making any research artefact available to the public and includes, but is not limited to, open access, open data, and open source. While open…
Survival Forests under Test: Impact of the Proportional Hazards Assumption on Prognostic and Predictive Forests for ALS Survival
Natalia Korepanova, Heidi Seibold, Verena Steffen +1
We investigate the effect of the proportional hazards assumption on prognostic and predictive models of the survival time of patients suffering from amyotrophic lateral sclerosis (…
Subgroup identification in dose-finding trials via model-based recursive partitioning
Marius Thomas, Björn Bornkamp, Heidi Seibold
An important task in early phase drug development is to identify patients, which respond better or worse to an experimental treatment. While a variety of different subgroup identif…
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…
Generalised Linear Model Trees with Global Additive Effects
Heidi Seibold, Torsten Hothorn, Achim Zeileis
Model-based trees are used to find subgroups in data which differ with respect to model parameters. In some applications it is natural to keep some parameters fixed globally for al…
Model-based Recursive Partitioning for Subgroup Analyses
Heidi Seibold, Achim Zeileis, Torsten Hothorn
The identification of patient subgroups with differential treatment effects is the first step towards individualised treatments. A current draft guideline by the EMA discusses pote…
Individual Treatment Effect Prediction for ALS Patients
Heidi Seibold, Achim Zeileis, Torsten Hothorn
A treatment for a complicated disease may be helpful for some but not all patients, which makes predicting the treatment effect for new patients important yet challenging. Here we…