scholarly journals A model-based correction for outcome reporting bias in meta-analysis

Biostatistics ◽  
2013 ◽  
Vol 15 (2) ◽  
pp. 370-383 ◽  
Author(s):  
J. Copas ◽  
K. Dwan ◽  
J. Kirkham ◽  
P. Williamson
Keyword(s):  
Meta Analysis ◽  
Reporting Bias ◽  
Outcome Reporting Bias ◽  
Outcome Reporting ◽  
Model Based

Outcome reporting bias and individual patient data meta-analysis: a case study in surgery

2001 ◽  
Vol 1 (S3) ◽  
Author(s):  
Kirsty McCormack ◽  
Neil Scott ◽  
Adrian Grant
Keyword(s):  
Individual Patient Data ◽  
Meta Analysis ◽  
Patient Data ◽  
Reporting Bias ◽  
Outcome Reporting Bias ◽  
Outcome Reporting

Model-based sensitivity analysis for outcome reporting bias in the meta analysis of benefit and harm outcomes

2017 ◽  
Vol 28 (3) ◽  
pp. 889-903 ◽  
Author(s):  
John Copas ◽  
Anthony Marson ◽  
Paula Williamson ◽  
Jamie Kirkham
Keyword(s):  
Meta Analysis ◽  
Partial Epilepsy ◽  
Risk Assessments ◽  
Reporting Bias ◽  
Drug Resistant ◽  
Cochrane Systematic Review ◽  
Outcome Reporting Bias ◽  
Outcome Reporting ◽  
Study Results ◽  
Test Treatment

Outcome reporting bias occurs when outcomes in research studies are selectively reported, the selection being influenced by the study results. For benefit outcomes, we have shown how risk assessments using the Outcome Reporting Bias in Trials risk classification scale can be used to calculate bias-adjusted treatment effect estimates. This paper presents a new and simpler version of the benefits method, and shows how it can be extended to cover the partial reporting and non-reporting of harm outcomes. Our motivating example is a Cochrane systematic review of 12 studies of Topiramate add-on therapy for drug-resistant partial epilepsy. Bias adjustments for partially reported or unreported outcomes suggest that the review has overestimated the benefits and underestimated the harms of the test treatment.

A multivariate meta-analysis approach for reducing the impact of outcome reporting bias in systematic reviews

2012 ◽  
Vol 31 (20) ◽  
pp. 2179-2195 ◽  
Author(s):  
Jamie J. Kirkham ◽  
Richard D. Riley ◽  
Paula R. Williamson
Keyword(s):  
Systematic Reviews ◽  
Meta Analysis ◽  
Reporting Bias ◽  
Analysis Approach ◽  
Outcome Reporting Bias ◽  
Outcome Reporting ◽  
The Impact

scholarly journals Multivariate meta-analysis helps examine the impact of outcome reporting bias in Cochrane rheumatoid arthritis reviews

2015 ◽  
Vol 68 (5) ◽  
pp. 542-550 ◽  
Author(s):  
Giacomo Frosi ◽  
Richard D. Riley ◽  
Paula R. Williamson ◽  
Jamie J. Kirkham
Keyword(s):  
Rheumatoid Arthritis ◽  
Meta Analysis ◽  
Reporting Bias ◽  
Outcome Reporting Bias ◽  
Outcome Reporting ◽  
The Impact

scholarly journals Correcting for outcome reporting bias in a meta-analysis: A meta-regression approach

2021 ◽  
Author(s):  
Robbie Cornelis Maria van Aert ◽  
Jelte M. Wicherts
Keyword(s):  
Effect Size ◽  
Meta Analysis ◽  
New Method ◽  
Reporting Bias ◽  
Average Effect ◽  
Outcome Reporting Bias ◽  
Monte Carlo Simulation Study ◽  
Average Effect Size ◽  
Outcome Reporting ◽  
Meta Regression

Outcome reporting bias (ORB) refers to the biasing effect caused by researchers selectively reporting outcomes based on their statistical significance. ORB leads to inflated average effect size estimates in a meta-analysis if only the outcome with the largest effect size is reported due to ORB. We propose a new method (CORB) to correct for ORB that includes an estimate of the variability of the outcomes' effect size as a moderator in a meta-regression model. An estimate of the variability of the outcomes' effect size can be computed by assuming a correlation among the outcomes. Results of a Monte-Carlo simulation study showed that effect size in meta-analyses may be severely overestimated without any correction for ORB. The CORB method accurately estimates effect size when overestimation caused by ORB is the largest. Applying the new method to a meta-analysis on the effect of playing violent video games on aggressive cognition showed that the average effect size estimate decreased when correcting for ORB. We recommend to routinely apply methods to correct for ORB in any meta-analysis. We provide annotated R code and functions to facilitate researchers to apply the CORB method.

scholarly journals Multivariate network meta-analysis to mitigate the effects of outcome reporting bias

2018 ◽  
Vol 37 (22) ◽  
pp. 3254-3266 ◽  
Author(s):  
Hyunsoo Hwang ◽  
Stacia M. DeSantis
Keyword(s):  
Meta Analysis ◽  
Reporting Bias ◽  
Outcome Reporting Bias ◽  
Outcome Reporting

Registry versus publication: discrepancy of primary outcomes and possible outcome reporting bias in child and adolescent mental health

2021 ◽  
Author(s):  
Nikolina Vrljičak Davidović ◽  
Luka Komić ◽  
Ivana Mešin ◽  
Mihaela Kotarac ◽  
Donald Okmažić ◽  
...  
Keyword(s):  
Mental Health ◽  
Adolescent Mental Health ◽  
Child And Adolescent ◽  
Reporting Bias ◽  
Outcome Reporting Bias ◽  
Outcome Reporting

scholarly journals Empirical evidence for outcome reporting bias in randomized clinical trials of acupuncture: comparison of registered records and subsequent publications

2015 ◽  
Vol 4 (1) ◽  
pp. 11-12
Author(s):  
Chun-Xiang Su ◽  
Mei Han ◽  
Jun Ren ◽  
Wen-Yuan Li ◽  
Shu-Jin Yue ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Empirical Evidence ◽  
Randomized Clinical Trials ◽  
Reporting Bias ◽  
Outcome Reporting Bias ◽  
Outcome Reporting
Sign in / Sign up

Export Citation Format

Share Document