activity
20122026
most citedModel-based dose finding under model uncertainty using general parametric models

165 citations · 312 across the 16 of their papers we have counts for

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13 papers · 1 filter

stat.ME2026

Estimands and estimation in trials with time trends

Marta Bofill Roig, Ekkehard Glimm, Kelly Van Lancker +1

In platform trials, model-based approaches typically estimate treatment effects conditional on calendar time. However, scientific and regulatory interest often lies in treatment ef…

stat.ME2026

Unbiased estimation in two-stage adaptive enrichment designs

Enyu Li, Nigel Stallard, Ekkehard Glimm +1

Recent advances in biomedical research have identified an increasing number of biomarkers associated with heterogeneity in patient responses to medical treatments. When a treatment…

stat.ME2026

Confidence intervals for two-stage adaptive designs with subpopulation selection

Enyu Li, Nigel Stallard, Ekkehard Glimm +2

We consider clinical trials in which an experimental treatment is compared with a control in pre-specified patient subpopulations. In such settings, adaptive enrichment designs all…

stat.ME2025

Exact matching as an alternative to propensity score matching

Ekkehard Glimm, Lillian Yau

The comparison of different medical treatments from observational studies or across different clinical studies is often biased by confounding factors such as systematic differences…

stat.ME2023★ 6 cited

Optimal allocation strategies in platform trials

Marta Bofill Roig, Ekkehard Glimm, Tobias Mielke +1

Platform trials are randomized clinical trials that allow simultaneous comparison of multiple interventions, usually against a common control. Arms to test experimental interventio…

stat.ME2022

Familywise error rate control for block response-adaptive randomization

Ekkehard Glimm, David Robertson

Response-adaptive randomization allows the probabilities of allocating patients to treatments in a clinical trial to change based on the previously observed response data, in order…

stat.ME2021★ 64 cited

On model-based time trend adjustments in platform trials with non-concurrent controls

Marta Bofill Roig, Pavla Krotka, Carl-Fredrik Burman +9

Platform trials can evaluate the efficacy of several treatments compared to a control. The number of treatments is not fixed, as arms may be added or removed as the trial progresse…

stat.ME2020

Connecting Instrumental Variable methods for causal inference to the Estimand Framework

Jack Bowden, Bjoern Bornkamp, Ekkehard Glimm +1

Causal inference methods are gaining increasing prominence in pharmaceutical drug development in light of the recently published addendum on estimands and sensitivity analysis in c…

stat.ME2016★ 15 cited

Optimal exact tests for multiple binary endpoints

Robin Ristl, Dong Xi, Ekkehard Glimm +1

In confirmatory clinical trials with small sample sizes, hypothesis tests based on asymptotic distributions are often not valid and exact non-parametric procedures are applied inst…

stat.ME2016★ 21 cited

On weighted parametric tests

Dong Xi, Ekkehard Glimm, Willi Maurer +1

We describe a general framework for weighted parametric multiple test procedures based on the closure principle. We utilize general weighting strategies that can reflect complex st…

stat.ME2013★ 165 cited

Model-based dose finding under model uncertainty using general parametric models

José Pinheiro, Björn Bornkamp, Ekkehard Glimm +1

Statistical methodology for the design and analysis of clinical Phase II dose response studies, with related software implementation, are well developed for the case of a normally…

stat.ME2013★ 3 cited

Some Notes on Blinded Sample Size Re-Estimation

Ekkehard Glimm, Jürgen Läuter

This note investigates a number of scenarios in which unadjusted testing following a blinded sample size re-estimation leads to type I error violations. For superiority testing, th…

stat.ME2012★ 2 cited

Exact Multivariate Tests - A New Effective Principle of Controlled Model Choice

Juergen Laeuter, Maciej Rosolowski, Ekkehard Glimm

High-dimensional tests are applied to find relevant sets of variables and relevant models. If variables are selected by analyzing the sums of products matrices and a corresponding…