Likelihood-based random-effects meta-analysis with few studies: empirical and simulation studies

Meta-analysis of Gaussian individual patient data: Two-stage or not two-stage?

(2018) Tim P. Morris et al.   STATISTICS IN MEDICINE

A comparison of seven random-effects models for meta-analyses that estimate the summary odds ratio

(2018) Dan Jackson et al.   STATISTICS IN MEDICINE

Methods for evidence synthesis in the case of very few studies

(2018) Ralf Bender et al.   Research Synthesis Methods

A design-by-treatment interaction model for network meta-analysis and meta-regression with integrated nested Laplace approximations

(2018) Burak Kürsad Günhan et al.   Research Synthesis Methods

A comparison of one-stage vs two-stage individual patient data meta-analysis methods: A simulation study

(2018) Evangelos Kontopantelis   Research Synthesis Methods

Contribution to the discussion of “When should meta-analysis avoid making hidden normality assumptions?” A Bayesian perspective

(2018) Christian Röver et al.   BIOMETRICAL JOURNAL

When should meta-analysis avoid making hidden normality assumptions?

(2018) Dan Jackson et al.   BIOMETRICAL JOURNAL

Methods to calculate uncertainty in the estimated overall effect size from a random-effects meta-analysis

(2018) Areti Angeliki Veroniki et al.   Research Synthesis Methods

Basics of meta-analysis:I2is not an absolute measure of heterogeneity

(2017) Michael Borenstein et al.   Research Synthesis Methods

Meta-analysis of two studies in the presence of heterogeneity with applications in rare diseases

(2016) Tim Friede et al.   BIOMETRICAL JOURNAL

Meta-analysis using individual participant data: one-stage and two-stage approaches, and why they may differ

(2016) Danielle L. Burke et al.   STATISTICS IN MEDICINE

Random effects meta-analysis: Coverage performance of 95%confidence and prediction intervals following REML estimation

(2016) Christopher Partlett et al.   STATISTICS IN MEDICINE

Meta-analysis of few small studies in orphan diseases

(2016) Tim Friede et al.   Research Synthesis Methods

Hartung-Knapp-Sidik-Jonkman approach and its modification for random-effects meta-analysis with few studies

(2015) Christian Röver et al.   BMC Medical Research Methodology

Misunderstandings aboutQand ‘Cochran'sQtest' in meta-analysis

(2015) David C. Hoaglin   STATISTICS IN MEDICINE

Conducting Meta-Analyses inRwith themetaforPackage

(2015) Wolfgang Viechtbauer   Journal of Statistical Software

The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method

(2014) Joanna IntHout et al.   BMC Medical Research Methodology

Predictive distributions for between-study heterogeneity and simple methods for their application in Bayesian meta-analysis

(2014) Rebecca M. Turner et al.   STATISTICS IN MEDICINE

Individual Participant Data Meta-Analysis for a Binary Outcome: One-Stage or Two-Stage?

(2013) Thomas P. A. Debray et al.   PLoS One

A Re-Analysis of the Cochrane Library Data: The Dangers of Unobserved Heterogeneity in Meta-Analyses

(2013) Evangelos Kontopantelis et al.   PLoS One

Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews

(2012) Rebecca M Turner et al.   INTERNATIONAL JOURNAL OF EPIDEMIOLOGY

Estimating heterogeneity variance in meta-analysis

(2012) Andrew L. Rukhin   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Comparison of One-Step and Two-Step Meta-Analysis Models Using Individual Patient Data

(2010) Thomas Mathew et al.   BIOMETRICAL JOURNAL

Random effects meta-analysis of event outcome in the framework of the generalized linear mixed model with applications in sparse data

(2010) Theo Stijnen et al.   STATISTICS IN MEDICINE

A re-evaluation of random-effects meta-analysis

(2008) Julian P. T. Higgins et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY