works on

From the 1 of 6 linked papers with an AI index.

collaborators

6 papers

stat.ME2026

Towards Best Practices for Covariate Adjustment in Regulatory Trials: From Fixed to Data-Adaptive Approaches

Laura B. Balzer, Lei Nie, Issa J. Dahabreh +15

The paper discusses how to improve precision in randomized clinical trials by using covariate adjustment, comparing traditional fixed parametric methods with flexible data‑adaptive…

stat.ME2026

One-step Outcome Imputation: An Alternative to Multiple Imputation

Andreas Nordland, Klaus K. Holst, David Redek +2

Missing outcomes in randomized controlled trials are often handled by multiple imputation (MI). Rubin's rules are routinely used to estimate standard errors but can fail to provide…

stat.ME2026

A framework for joint assessment of a terminal event and a score existing only in the absence of the terminal event

Klaus Kähler Holst, Andreas Nordland, Julie Funch Furberg +2

Analysis of data from randomized controlled trials in vulnerable populations requires special attention when assessing treatment effect by a score measuring, e.g., disease stage or…

stat.ME2026

A non-parametric approach for estimating the correlation between log-rank test statistics with applications to a conjunctive power calculation

Anne Lyngholm Soerensen, Paul Blanche, Henrik Ravn +1

We present a method for estimating the correlation between log-rank test statistics evaluating separate null hypotheses for two time-to-event endpoints. The correlation is estimate…

stat.ME2025

A general approach to construct powerful tests for intersections of one-sided null-hypotheses based on influence functions

Christian Bressen Pipper, Andreas Nordland, Klaus Kähler Holst

Testing intersections of null-hypotheses is an integral part of closed testing procedures for assessing multiple null-hypotheses under family-wise type 1 error control. Popular int…

stat.ME2025

Causal interpretation of the sibling comparison and its relation to the cross-over design

Simon Bang Kristensen, Christian Bressen Pipper, Jacob von Bornemann Hjelmborg

The intuitive motivation for employing a sibling comparison design is to adjust for confounding that is constant within families. Such confounding can be caused by variables that o…