SynthesisBMC medical research methodology2020
Laplace approximation, penalized quasi-likelihood, and adaptive Gauss-Hermite quadrature for generalized linear mixed models: towards meta-analysis of binary outcome with sparse data.
Synthesis in BMC medical research methodology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.
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Who cites it
27 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Including randomized and non-randomized studies of interventions in evidence synthesis for harms: a meta-epidemiological study.BMC medicine · 2026Pooled it
- Performance of several types of beta-binomial models in comparison to standard approaches for meta-analyses with very few studies.BMC medical research methodology · 2022Pooled it
- Bayesian Methods for Meta-Analyses of Binary Outcomes: Implementations, Examples, and Impact of Priors.International journal of environmental research and public health · 2021Pooled it
- A reproducible, diagnostic-guided hybrid Laplace workflow for generalized linear mixed models.MethodsX · 2026Article
- Fatigue Symptoms Influence Effort-Based Decision-Making in Major Depressive Disorder.Biological psychiatry global open science · 2026Article
- Toward Evidence Synthesis of Adverse Events in Imbalanced Time-to-Event Data.Journal of evidence-based medicine · 2026Article
- Statistical models to characterize colon tumor stiffness heterogeneity through representative atomic force microscopy maps.Scientific reports · 2026Article
- Alternative tests and measures for between-study inconsistency in meta-analysis.BMC medical research methodology · 2025Article
- Fatigue Symptoms Influence Effort-Based Decision-Making in Major Depressive Disorder.medRxiv : the preprint server for health sciences · 2025Article
- Random-effects meta-analysis models for pooling rare events data: a comparison between frequentist and bayesian methods.BMC medical research methodology · 2025Article
- The Neurobiology of Cognitive Fatigue and Its Influence on Effort-Based Choice.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Advancing Interpretable Regression Analysis for Binary Data: A Novel Distributed Algorithm Approach.Statistics in medicine · 2024Article
- An evaluation of computational methods for aggregate data meta-analyses of diagnostic test accuracy studies.BMC medical research methodology · 2024Article
- Federated generalized linear mixed models for collaborative genome-wide association studies.iScience · 2023Article
- Intimate Partner Violence During COVID-19 Restrictions: A Study of 30 Countries From the I-SHARE Consortium.Journal of interpersonal violence · 2023Article
- Examining the risk factors for overweight and obesity among women in Ghana: A multilevel perspective.Heliyon · 2023Article
- Measuring the impact of zero-cases studies in evidence synthesis practice using the harms index and benefits index (Hi-Bi).BMC medical research methodology · 2023Article
- Big Data in Gastroenterology Research.International journal of molecular sciences · 2023Review
- An empirical comparison of the harmful effects for randomized controlled trials and non-randomized studies of interventions.Frontiers in pharmacology · 2023Article
- Ontogenetic patterns in human frontal sinus shape: A longitudinal study using elliptical Fourier analysis.Journal of anatomy · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundIn meta-analyses of a binary outcome, double zero events in some studies cause a critical methodology problem. The generalized linear mixed model (GLMM) has been proposed as a valid statistical tool for pooling such data. Three parameter estimation methods, including the Laplace approximation (LA), penalized quasi-likelihood (PQL) and adaptive Gauss-Hermite quadrature (AGHQ) were frequently used in the GLMM. However, the performance of GLMM via these estimation methods is unclear in meta-analysis with zero events.
methodsA simulation study was conducted to compare the performance. We fitted five random-effects GLMMs and estimated the results through the LA, PQL and AGHQ methods, respectively. Each scenario conducted 20,000 simulation iterations. The data from Cochrane Database of Systematic Reviews were collected to form the simulation settings. The estimation methods were compared in terms of the convergence rate, bias, mean square error, and coverage probability.
resultsOur results suggested that when the total events were insufficient in either of the arms, the GLMMs did not show good point estimation to pool studies of rare events. The AGHQ method did not show better properties than the LA estimation in terms of convergence rate, bias, coverage, and possibility to produce very large odds ratios. In addition, although the PQL had some advantages, it was not the preferred option due to its low convergence rate in some situations, and the suboptimal point and variance estimation compared to the LA.
conclusionThe GLMM is an alternative for meta-analysis of rare events and is especially useful in the presence of zero-events studies, while at least 10 total events in both arms is recommended when employing GLMM for meta-analysis. The penalized quasi-likelihood and adaptive Gauss-Hermite quadrature are not superior to the Laplace approximation for rare events and thus they are not recommended.
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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.