Cover Image

The bipartite structure of treatment-trial networks reveals the flow of information in network meta-analysis

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Davies, Annabel L
Format:	Preprint
Published:	2025
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Degree irregularity and rank probability bias in network meta-analysis
by: Davies, Annabel L, et al.
Published: (2020)

A complex meta-regression model to identify effective features of interventions from multi-arm, multi-follow-up trials
by: Davies, Annabel L, et al.
Published: (2024)

Mapping between measurement scales in meta-analysis, with application to measures of body mass index in children
by: Davies, Annabel L, et al.
Published: (2024)

Disentangling the structure of ecological bipartite networks from observation processes
by: Anakok, Emre, et al.
Published: (2022)

Creating treatment and component hierarchies in component network meta-analysis
by: Wigle, Augustine, et al.
Published: (2026)

Network Meta-analysis and Diffusion
by: Rücker, Gerta, et al.
Published: (2026)

Publication bias adjustment in network meta-analysis: an inverse probability weighting approach using clinical trial registries
by: Huang, Ao, et al.
Published: (2024)

Producing treatment hierarchies in network meta-analysis using probabilistic models and treatment-choice criteria
by: Evrenoglou, Theodoros, et al.
Published: (2024)

Biclustering bipartite networks via extended Mixture of Latent Trait Analyzers
by: Failli, Dalila, et al.
Published: (2024)

Improving exponential-family random graph models for bipartite networks
by: Stivala, Alex, et al.
Published: (2025)

Bayesian unanchored additive models for component network meta-analysis
by: Wigle, Augustine, et al.
Published: (2025)

Multilevel mixtures of latent trait analyzers for clustering multi-layer bipartite networks
by: Failli, Dalila, et al.
Published: (2023)

Community detection in multi-layer bipartite networks
by: Qing, Huan
Published: (2024)

Sensitivity analysis for contamination in egocentric-network randomized trials with interference
by: Weinstein, Bar, et al.
Published: (2026)

Influence analyses of "designs" for evaluating inconsistency in network meta-analysis
by: Sasaki, Kotaro, et al.
Published: (2024)

A stopping rule for randomly sampling bipartite networks with fixed degree sequences
by: Neal, Zachary P.
Published: (2023)

Individual-centered partial information in social networks
by: Han, Xiao, et al.
Published: (2020)

Multilevel network meta-regression for general likelihoods: synthesis of individual and aggregate data with applications to survival analysis
by: Phillippo, David M., et al.
Published: (2024)

1-truncated C-vine copula mixed models for network meta-analysis of multiple diagnostic tests
by: Nikoloulopoulos, Aristidis K.
Published: (2026)

Rank-based estimators of global treatment effects for cluster randomized trials with multiple endpoints
by: Smith, E. Davies, et al.
Published: (2024)

Community detection in bipartite signed networks is highly dependent on parameter choice
by: Candellone, Elena, et al.
Published: (2024)

Causal inference with misspecified network interference structure
by: Weinstein, Bar, et al.
Published: (2023)

Transportability of aggregate trial results to an external environment in causally interpretable meta-analysis
by: Le, Tran Trong Khoi, et al.
Published: (2024)

Path-Based Approach for Detecting and Assessing Inconsistency in Network Meta-Analysis: A Novel Method
by: Tahmasebi, Noosheen R., et al.
Published: (2025)

On a penalised likelihood approach for joint modelling of longitudinal covariates and partly interval-censored data -- an application to the Anti-PD1 brain collaboration trial
by: Webb, Annabel, et al.
Published: (2024)

Simultaneous global and local clustering in multiplex networks with covariate information
by: Corneck, Joshua, et al.
Published: (2025)

Identification and efficient estimation of compliance and network causal effects in cluster-randomized trials
by: Cheng, Chao, et al.
Published: (2025)

The causal effects of modified treatment policies under network interference
by: Balkus, Salvador V., et al.
Published: (2024)

Meta-analysis and network meta-analysis of time-to-event outcomes with non-proportional hazards: a Bayesian time-varying hazard ratio approach
by: Owen, Rhiannon K, et al.
Published: (2026)

Scalable computation of the maximum flow in large brain connectivity networks
by: Qian, Jingyun, et al.
Published: (2024)

Connections as treatment: causal inference with edge interventions in networks
by: Chen, Shuli, et al.
Published: (2026)

Utilizing subgroup information in random-effects meta-analysis of few studies
by: Huang, Ao, et al.
Published: (2025)

Redefining shared information: a heterogeneity-adaptive framework for meta-analysis
by: Davis, Elizabeth M., et al.
Published: (2026)

Sparse two-stage Bayesian meta-analysis for individualized treatments
by: Shen, Junwei, et al.
Published: (2024)

On inference for modularity statistics in structured networks
by: Mitra, Anirban, et al.
Published: (2024)

NExON-Bayes: A Bayesian approach to network estimation informed by ordinal covariates
by: Feest, Joseph, et al.
Published: (2025)

Co-factor analysis of citation networks
by: Hayes, Alex, et al.
Published: (2024)

Community-level core-periphery structures in collaboration networks
by: Geremia, Sara, et al.
Published: (2025)

A studentized permutation test for the treatment effect in individual participant data meta-analysis
by: Tran, Phuc Thien, et al.
Published: (2025)

Convergence guarantees for response prediction for latent structure network time series
by: Acharyya, Aranyak, et al.
Published: (2025)