:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Nießl, Christina, Herrmann, Moritz, Wiedemann, Chiara, Casalicchio, Giuseppe, Boulesteix, Anne-Laure
Format:	Preprint
Published:	2021
Subjects:	Methodology
Online Access:	https://arxiv.org/abs/2106.02447
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Explaining the optimistic performance evaluation of newly proposed methods: a cross-design validation experiment
by: Nießl, Christina, et al.
Published: (2022)

Rethinking the handling of method failure in comparison studies
by: Wünsch, Milena, et al.
Published: (2024)

On "Confirmatory" Methodological Research in Statistics and Related Fields
by: Lange, F. J. D., et al.
Published: (2025)

Statistical parametric simulation studies based on real data
by: Sauer, Christina, et al.
Published: (2025)

Outlier Detection in Mendelian Randomisation
by: Mandl, Maximilian M, et al.
Published: (2025)

Beyond algorithm hyperparameters: on preprocessing hyperparameters and associated pitfalls in machine learning applications
by: Sauer, Christina, et al.
Published: (2024)

permApprox: a general framework for accurate permutation p-value approximation
by: Peschel, Stefanie, et al.
Published: (2026)

Understanding overfitting in random forest for probability estimation: a visualization and simulation study
by: Barreñada, Lasai, et al.
Published: (2024)

To tweak or not to tweak. How exploiting flexibilities in gene set analysis leads to over-optimism
by: Wünsch, Milena, et al.
Published: (2024)

Addressing researcher degrees of freedom through minP adjustment
by: Mandl, Maximilian M, et al.
Published: (2024)

Communicating results in trials with multiple hypotheses or adaptive design features
by: Asikanius, Elina, et al.
Published: (2026)

How trace plots help interpret meta-analysis results
by: Röver, Christian, et al.
Published: (2023)

Transportability of aggregate trial results to an external environment in causally interpretable meta-analysis
by: Le, Tran Trong Khoi, et al.
Published: (2024)

Accounting for multiplicity in machine learning benchmark performance
by: Møllersen, Kajsa, et al.
Published: (2023)

To Tweak or Not to Tweak. How Exploiting Flexibilities in Gene Set Analysis Leads to Overoptimism
by: Milena Wünsch, et al.
Published: (2024)

A Guide to Feature Importance Methods for Scientific Inference
by: Ewald, Fiona Katharina, et al.
Published: (2024)

A maximin optimal approach for sampling designs in two-phase studies
by: Wang, Ruoyu, et al.
Published: (2023)

Single CASANOVA? Not in multiple comparisons
by: Dormuth, Ina, et al.
Published: (2024)

Causal interpretation of the sibling comparison and its relation to the cross-over design
by: Kristensen, Simon Bang, et al.
Published: (2025)

Revisiting the apparent discrepancy between the frequentist and Bayesian interpretation of an adaptive design
by: Kristensen, Simon Bang, et al.
Published: (2025)

Gibbs optimal design of experiments
by: Overstall, Antony M., et al.
Published: (2023)

CVXSADes: a stochastic algorithm for constructing optimal exact regression designs with single or multiple objectives
by: Yeh, Chi-Kuang, et al.
Published: (2024)

Low-order outcomes and clustered designs: combining design and analysis for causal inference under network interference
by: Eichhorn, Matthew, et al.
Published: (2024)

Position: Why We Must Rethink Empirical Research in Machine Learning
by: Herrmann, Moritz, et al.
Published: (2024)

Identifiable and interpretable nonparametric factor analysis
by: Xu, Maoran, et al.
Published: (2023)

Do-search -- a tool for causal inference and study design with multiple data sources
by: Karvanen, Juha, et al.
Published: (2020)

Two-level D- and A-optimal designs of Ehlich type with run sizes three more than a multiple of four
by: Hameed, Mohammed Saif Ismail, et al.
Published: (2025)

A Simulation Study to Compare Inferential Properties when Modelling Ordinal Outcomes: The Case for the (Plain but Robust) Proportional Odds Model
by: Inerle, Stefan, et al.
Published: (2026)

Estimands and cumulative incidence function regression in clinical trials: some new results on interpretability and robustness
by: Bühler, Alexandra, et al.
Published: (2024)

Transporting results from a trial to an external target population when trial participation impacts adherence
by: Ross, Rachael K., et al.
Published: (2025)

Causally-interpretable meta-analysis using aggregate data
by: Shi, Qingyang, et al.
Published: (2026)

Two-level D- and A-optimal main-effects designs with run sizes one and two more than a multiple of four
by: Hameed, Mohammed Saif Ismail, et al.
Published: (2024)

Utility-based optimization of Fujikawa's basket trial design -- Pre-specified protocol of a comparison study
by: Sauer, Lukas D, et al.
Published: (2024)

An adaptive design for optimizing treatment assignment in randomized clinical trials
by: Zhang, Wei, et al.
Published: (2025)

Fixed-budget optimal designs for multi-fidelity computer experiments
by: Chen, Gecheng, et al.
Published: (2024)

Estimating optimal interpretable individualized treatment regimes from a classification perspective using adaptive LASSO
by: Zhang, Yunshu, et al.
Published: (2026)

Confirmatory adaptive group sequential designs for clinical trials with multiple time-to-event outcomes in Markov models
by: Danzer, Moritz Fabian, et al.
Published: (2023)

From RNA sequencing measurements to the final results: a practical guide to navigating the choices and uncertainties of gene set analysis
by: Wünsch, Milena, et al.
Published: (2023)

From RNA sequencing measurements to the final results: A practical guide to navigating the choices and uncertainties of gene set analysis
by: Milena Wünsch, et al.
Published: (2024)

Integration of aggregated data in causally interpretable meta-analysis by inverse weighting
by: Vo, Tat-Thang, et al.
Published: (2025)