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20212026
most citedMeta-analysis models relaxing the random effects normality assumption: methodological systematic review and simulation study

1 citations · 1 across the 5 of their papers we have counts for

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stat.ME2026

Distinguishing case-mix from context heterogeneity in prognostic regression model synthesis settings

Max Behrens, Janis M. Nolde, Eleni Papakonstantinou +6

Prognostic regression models often synthesize data from multiple sites, whether within a multi-site study, across federated settings, or in individual participant data meta-analysi…

stat.ME2026

Assessing the Impact of Model Assumptions in Network Meta-Regression: A Simulation Study

Nana-adjoa Kwarteng, Guido Schwarzer, Adriani Nikolakopoulou +1

Network meta-regression (NMR) extends network meta-analysis (NMA) by synthesizing evidence on multiple treatments while adjusting for potential effect modifiers. By accounting for…

stat.ME20241 cited

Meta-analysis models relaxing the random effects normality assumption: methodological systematic review and simulation study

Kanella Panagiotopoulou, Theodoros Evrenoglou, Christopher H Schmid +2

Random effects meta-analysis is widely used for synthesizing studies under the assumption that underlying effects come from a normal distribution. However, under certain conditions…

stat.ME2024

Producing treatment hierarchies in network meta-analysis using probabilistic models and treatment-choice criteria

Theodoros Evrenoglou, Adriani Nikolakopoulou, Guido Schwarzer +2

A key output of network meta-analysis (NMA) is the relative ranking of treatments; nevertheless, it has attracted substantial criticism. Existing ranking methods often lack clear i…

stat.ME2021

Network meta-analysis of rare events using penalized likelihood regression

Theodoros Evrenoglou, Ian White, Sivem Afach +2

Network meta-analysis (NMA) of rare events has attracted little attention in the literature. Until recently, networks of interventions with rare events were analyzed using the inve…