activity
20162022
most citedMetaStan: An R package for Bayesian (model-based) meta-analysis using Stan

4 citations · 5 across the 9 of their papers we have counts for

collaborators
Showing 2018Show all

8 papers · 1 filter

stat.AP2018

A Bayesian time-to-event pharmacokinetic model for sequential phase I dose-escalation trials with multiple schedules

Burak Kürsad Günhan, Sebastian Weber, Abdelkader Seroutou +1

Phase I dose-escalation trials constitute the first step in investigating the safety of potentially promising drugs in humans. Conventional methods for phase I dose-escalation tria…

stat.AP2018

Recent advances in methodology for clinical trials in small populations: the InSPiRe project

T. Friede, M. Posch, S. Zohar +19

Where there are a limited number of patients, such as in a rare disease, clinical trials in these small populations present several challenges, including statistical issues. This l…

stat.ME2018

Contribution to the discussion of "When should meta-analysis avoid making hidden normality assumptions?": A Bayesian perspective

Christian Röver, Tim Friede

Contribution to the discussion of "When should meta-analysis avoid making hidden normality assumptions?" by Dan Jackson and Ian R. White (2018; https://doi.org/10.1002/bimj.2018000…

stat.AP2018

Meta-analysis of few studies involving rare events

Burak Kürsad Günhan, Christian Röver, Tim Friede

Meta-analyses of clinical trials targeting rare events face particular challenges when the data lack adequate numbers of events for all treatment arms. Especially when the number o…

stat.ME2018

Likelihood-based meta-analysis with few studies: Empirical and simulation studies

Svenja E. Seide, Christian Röver, Tim Friede

Standard random-effects meta-analysis methods perform poorly when applied to few studies only. Such settings however are commonly encountered in practice. It is unclear, whether or…

stat.ME2018

Dynamically borrowing strength from another study through shrinkage estimation

Christian Röver, Tim Friede

Meta-analytic methods may be used to combine evidence from different sources of information. Quite commonly, the normal-normal hierarchical model (NNHM) including a random-effect t…