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stat.ME2026

Introducing precision-weighted bias as a performance measure to inform the inclusion of adaptive designs in meta-analysis

Martin Law, David S. Robertson, Sofia S. Villar +4

We propose a novel, intuitive measure of statistical performance: precision-weighted bias. Precision-weighted bias is defined as the unconditional bias of an estimator weighted by…

stat.ME2026

Safety-Driven Response Adaptive Randomisation: An Application in Non-inferiority Oncology Trials

Maria Vittoria Chiaruttini, Lukas Pin, Sofia S. Villar

The majority of response-adaptive randomisation (RAR) designs in the literature rely on efficacy data to guide dynamic patient allocation. However, their applicability becomes limi…

stat.ME2025

Thompson, Ulam, or Gauss? Multi-criteria recommendations for posterior probability computation methods in Bayesian response-adaptive trials

Daniel Kaddaj, Stef Baas, Edwin Y. N. Tang +3

Bayesian adaptive designs enable flexible clinical trials by adapting features based on accumulating data. Among these, Bayesian Response-Adaptive Randomization (BRAR) skews patien…

stat.ME2025

Informed Burn-In Decisions in RAR: Harmonizing Adaptivity and Inferential Precision Based on Study Setting

Lukas Pin, Stef Baas, Gianmarco Caruso +2

Response-Adaptive Randomization (RAR) is recognized for its potential to deliver improvements in patient benefit. However, the utility of RAR is contingent on regularization method…

stat.ME2025

Is 1:1 Always Most Powerful? Why Careful Determination of Allocation Ratios Matters in Trial Design

Lukas Pin, Stef Baas, David S. Robertson +1

The principle of allocating an equal number of patients to each arm in a randomized controlled trial remains widely believed to be optimal for maximising statistical power. However…

stat.ME2025

A burn-in(g) question: How long should an initial equal randomization stage be before Bayesian response-adaptive randomization?

Edwin Y. N. Tang, Stef Baas, Daniel Kaddaj +3

Response-adaptive randomization (RAR) can increase participant benefit in clinical trials, but also complicates statistical analysis. The burn-in period (a non-adaptive initial sta…