980 citations · 3k across the 31 of their papers we have counts for
14 papers · 1 filter
Utilizing subgroup information in random-effects meta-analysis of few studies
Ao Huang, Christian Röver, Tim Friede
Random-effects meta-analyses are widely used for evidence synthesis in medical research. However, conventional methods based on large-sample approximations often exhibit poor perfo…
Investigating the heterogeneity of "study twins"
Christian Röver, Tim Friede
Meta-analyses are commonly performed based on random-effects models, while in certain cases one might also argue in favour of a common-effect model. One such case may be given by t…
How trace plots help interpret meta-analysis results
Christian Röver, David Rindskopf, Tim Friede
The trace plot is seldom used in meta-analysis, yet it is a very informative plot. In this article we define and illustrate what the trace plot is, and discuss why it is important.…
Double arcsine transform not appropriate for meta-analysis
Christian Röver, Tim Friede
The variance-stabilizing Freeman-Tukey double arcsine transform was originally proposed for inference on single proportions. Subsequently, its use has been suggested in the context…
Summarizing empirical information on between-study heterogeneity for Bayesian random-effects meta-analysis
Christian Röver, Sibylle Sturtz, Jona Lilienthal +2
In Bayesian meta-analysis, the specification of prior probabilities for the between-study heterogeneity is commonly required, and is of particular benefit in situations where only…
A straightforward meta-analysis approach for oncology phase I dose-finding studies
Christian Röver, Moreno Ursino, Tim Friede +1
Phase I early-phase clinical studies aim at investigating the safety and the underlying dose-toxicity relationship of a drug or combination. While little may still be known about t…
On weakly informative prior distributions for the heterogeneity parameter in Bayesian random-effects meta-analysis
Christian Röver, Ralf Bender, Sofia Dias +5
The normal-normal hierarchical model (NNHM) constitutes a simple and widely used framework for meta-analysis. In the common case of only few studies contributing to the meta-analys…
Bounds for the weight of external data in shrinkage estimation
Christian Röver, Tim Friede
Shrinkage estimation in a meta-analysis framework may be used to facilitate dynamical borrowing of information. This framework might be used to analyze a new study in the light of…
Using phase II data for the analysis of phase III studies: an application in rare diseases
Simon Wandel, Beat Neuenschwander, Tim Friede +1
Clinical research and drug development in orphan diseases is challenging, since large-scale randomized studies are difficult to conduct. Formally synthesizing the evidence is there…
Meta-analysis of two studies in the presence of heterogeneity with applications in rare diseases
Tim Friede, Christian Röver, Simon Wandel +1
Random-effects meta-analyses are used to combine evidence of treatment effects from multiple studies. Since treatment effects may vary across trials due to differences in study cha…
Meta-analysis of few small studies in orphan diseases
Tim Friede, Christian Röver, Simon Wandel +1
Meta-analyses in orphan diseases and small populations generally face particular problems including small numbers of studies, small study sizes, and heterogeneity of results. Howev…
Hartung-Knapp-Sidik-Jonkman approach and its modification for random-effects meta-analysis with few studies
Christian Röver, Guido Knapp, Tim Friede
BACKGROUND: Random-effects meta-analysis is commonly performed by first deriving an estimate of the between-study variation, the heterogeneity, and subsequently using this as the b…
Evidence synthesis for count distributions based on heterogeneous and incomplete aggregated data
Christian Röver, Stefan Andreas, Tim Friede
The analysis of count data is commonly done using Poisson models. Negative binomial models are a straightforward and readily motivated generalization for the case of overdispersed…
Modelling coloured residual noise in gravitational-wave signal processing
Christian Röver, Renate Meyer, Nelson Christensen
We introduce a signal processing model for signals in non-white noise, where the exact noise spectrum is a priori unknown. The model is based on a Student's t distribution and cons…