ArticleStatistical methods in medical research2017
Bayesian hierarchical models for network meta-analysis incorporating nonignorable missingness.
Article in Statistical methods in medical research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed.
- Tipping point analysis in network meta-analysis.Research synthesis methods · 2025Article
- Risk of Bias in Network Meta-Analysis (RoB NMA) tool.BMJ (Clinical research ed.) · 2025Article
- Choice of Link Functions for Generalized Linear Mixed Models in Meta-Analyses of Proportions.Research methods in medicine & health sciences · 2025Article
- Bayesian hierarchical model-based network meta-analysis to overcome survival extrapolation challenges caused by data immaturity.Journal of comparative effectiveness research · 2023Article
- BRIDGING RANDOMIZED CONTROLLED TRIALS AND SINGLE-ARM TRIALS USING COMMENSURATE PRIORS IN ARM-BASED NETWORK META-ANALYSIS.The annals of applied statistics · 2021Article
- A variance shrinkage method improves arm-based Bayesian network meta-analysis.Statistical methods in medical research · 2021Article
- A Bayesian Hierarchical CACE Model Accounting for Incomplete Noncompliance With Application to a Meta-analysis of Epidural Analgesia on Cesarean Section.Journal of the American Statistical Association · 2021Article
- Fragility index of network meta-analysis with application to smoking cessation data.Journal of clinical epidemiology · 2020Article
- Bayesian Network Meta-analysis of Multiple Outcomes in Dental Research.The journal of evidence-based dental practice · 2020Article
- A Bayesian Vector Autoregressive Model with Nonignorable Missingness in Dependent Variables and Covariates: Development, Evaluation, and Application to Family Processes.Structural equation modeling : a multidisciplinary journal · 2020Article
- A comparison of arm-based and contrast-based models for network meta-analysis.Statistics in medicine · 2019Article
- Bayesian hierarchical methods for meta-analysis combining randomized-controlled and single-arm studies.Statistical methods in medical research · 2019Article
- Bayesian Modeling and Inference for Nonignorably Missing Longitudinal Binary Response Data with Applications to HIV Prevention Trials.Statistica Sinica · 2018Article
- Performing Arm-Based Network Meta-Analysis in R with the pcnetmeta Package.Journal of statistical software · 2017Article
- An investigation of the impact of using different methods for network meta-analysis: a protocol for an empirical evaluation.Systematic reviews · 2017Article
- CORR InsightsClinical orthopaedics and related research · 2017Article
- Extending DerSimonian and Laird's methodology to perform network meta-analyses with random inconsistency effects.Statistics in medicine · 2016Article
- Rejoinder to the discussion of "a Bayesian missing data framework for generalized multiple outcome mixed treatment comparisons," by S. Dias and A. E. Ades.Research synthesis methods · 2016Article
- Article
- Detecting outlying trials in network meta-analysis.Statistics in medicine · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Network meta-analysis expands the scope of a conventional pairwise meta-analysis to simultaneously compare multiple treatments, synthesizing both direct and indirect information and thus strengthening inference. Since most of trials only compare two treatments, a typical data set in a network meta-analysis managed as a trial-by-treatment matrix is extremely sparse, like an incomplete block structure with significant missing data. Zhang et al. proposed an arm-based method accounting for correlations among different treatments within the same trial and assuming that absent arms are missing at random. However, in randomized controlled trials, nonignorable missingness or missingness not at random may occur due to deliberate choices of treatments at the design stage. In addition, those undertaking a network meta-analysis may selectively choose treatments to include in the analysis, which may also lead to missingness not at random. In this paper, we extend our previous work to incorporate missingness not at random using selection models. The proposed method is then applied to two network meta-analyses and evaluated through extensive simulation studies. We also provide comprehensive comparisons of a commonly used contrast-based method and the arm-based method via simulations in a technical appendix under missing completely at random and missing at random.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.