165 citations · 312 across the 16 of their papers we have counts for
21 papers
On relations between the Cochran--Mantel--Haenszel test and Augmented Inverse Probability Weighting
Ekkehard Glimm
This note revisits the Cochran-Mantel-Haenszel (CMH) test in light of the increasing use of causal inference methods in clinical trials. It shows that the CMH test statistic can be…
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…
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…
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…
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…
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…
Designing an exploratory phase 2b platform trial in NASH with correlated, co-primary binary endpoints
Elias Laurin Meyer, Peter Mesenbrink, Nicholas A. Di Prospero +5
Non-alcoholic steatohepatitis (NASH) is the progressive form of nonalcoholic fatty liver disease (NAFLD) and a disease with high unmet medical need. Platform trials provide great b…
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…
CohortPlat: Simulation of cohort platform trials investigating combination therapies
Elias Laurin Meyer, Peter Mesenbrink, Cornelia Dunger-Baldauf +2
Platform trials have gained a lot of attention recently as a possible remedy for time-consuming classical two-arm randomized controlled trials, especially in early phase drug devel…
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…
Geometric approaches to assessing the numerical feasibility for conducting matching-adjusted indirect comparisons
Ekkehard Glimm, Lillian Yau
We discuss how to handle matching-adjusted indirect comparison (MAIC) from a data analyst's perspective. We introduce several multivariate data analysis methods to assess the appro…
Decision rules for identifying combination therapies in open-entry, randomized controlled platform trials
Elias Laurin Meyer, Peter Mesenbrink, Cornelia Dunger-Baldauf +3
Platform trials have become increasingly popular for drug development programs, attracting interest from statisticians, clinicians and regulatory agencies. Many statistical questio…
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…
Blinded sample size re-estimation in equivalence testing
Ekkehard Glimm, Lillian Yau, Heike Woehling
This paper investigates type I error violations that occur when blinded sample size reviews are applied in equivalence testing. We give a derivation which explains why such violati…
Confidence intervals with maximal average power
Christian Bartels, Johanna Mielke, Ekkehard Glimm
We propose a frequentist testing procedure that maintains a defined coverage and is optimal in the sense that it gives maximal power to detect deviations from a null hypothesis whe…
Group sequential designs for negative binomial outcomes
Tobias Mütze, Ekkehard Glimm, Heinz Schmidli +1
Count data and recurrent events in clinical trials, such as the number of lesions in magnetic resonance imaging in multiple sclerosis, the number of relapses in multiple sclerosis,…
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…
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…
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…
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…
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…