A comparison of seven random-effects models for meta-analyses that estimate the summary odds ratio
Published 2018 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A comparison of seven random-effects models for meta-analyses that estimate the summary odds ratio
Authors
Keywords
-
Journal
STATISTICS IN MEDICINE
Volume 37, Issue 7, Pages 1059-1085
Publisher
Wiley
Online
2018-01-10
DOI
10.1002/sim.7588
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A general framework for the use of logistic regression models in meta-analysis
- (2016) Mark C Simmonds et al. STATISTICAL METHODS IN MEDICAL RESEARCH
- Low-event-rate meta-analyses of clinical trials: implementing good practices
- (2016) Jonathan J. Shuster et al. STATISTICS IN MEDICINE
- 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
- Meta-analysis of clinical trials with rare events
- (2015) Dankmar Böhning et al. BIOMETRICAL JOURNAL
- Fitting Linear Mixed-Effects Models Usinglme4
- (2015) Douglas Bates et al. Journal of Statistical Software
- Extending DerSimonian and Laird's methodology to perform network meta-analyses with random inconsistency effects
- (2015) Dan Jackson et al. STATISTICS IN MEDICINE
- Misunderstandings aboutQand ‘Cochran'sQtest' in meta-analysis
- (2015) David C. Hoaglin STATISTICS IN MEDICINE
- Rejoinder to the discussion of “a Bayesian missing data framework for generalized multiple outcome mixed treatment comparisons,” by S. Dias and A. E. Ades
- (2015) Hwanhee Hong et al. Research Synthesis Methods
- Methods to estimate the between-study variance and its uncertainty in meta-analysis
- (2015) Areti Angeliki Veroniki et al. Research Synthesis Methods
- Absolute or relative effects? Arm-based synthesis of trial data
- (2015) S. Dias et al. Research Synthesis Methods
- Conducting Meta-Analyses inRwith themetaforPackage
- (2015) Wolfgang Viechtbauer Journal of Statistical Software
- Elucidating the Foundations of Statistical Inference with 2 x 2 Tables
- (2015) Leena Choi et al. PLoS One
- Statistical methods for meta-analyses including information from studies without any events-add nothing to nothing and succeed nevertheless
- (2014) O. Kuss STATISTICS IN MEDICINE
- A sensitivity analysis framework for the treatment effect measure used in the meta-analysis of comparative binary data from randomised controlled trials
- (2012) Dan Jackson et al. STATISTICS IN MEDICINE
- Characteristics of meta-analyses and their component studies in the Cochrane Database of Systematic Reviews: a cross-sectional, descriptive analysis
- (2011) Jonathan Davey et al. BMC Medical Research Methodology
- Confidence intervals for a random-effects meta-analysis based on Bartlett-type corrections
- (2011) Hisashi Noma STATISTICS IN MEDICINE
- Hans van Houwelingen and the Art of Summing up
- (2010) Stephen Senn 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
- Extending DerSimonian and Laird's methodology to perform multivariate random effects meta-analyses
- (2009) Dan Jackson 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
- A re-evaluation of the ‘quantile approximation method’ for random effects meta-analysis
- (2008) Dan Jackson et al. STATISTICS IN MEDICINE
- Why add anything to nothing? The arcsine difference as a measure of treatment effect in meta-analysis with zero cells
- (2008) Gerta Rücker et al. STATISTICS IN MEDICINE
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationPublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More