Adjusting for publication bias in the presence of heterogeneity

By N. Terrin, Christopher H. Schmid, Joseph Lau, Ingram Olkin. Statistics in Medicine, 2003

790 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d43f8fa6ebee9939cd2ce210bdbf69848c0588fa

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Citations in the corpus

Performance of the trim and fill method in the presence of publication bias and between‐study heterogeneity (2007, methodology): “In fact, it can impute studies that have unrealistic effects [15].”
A systematic review of the incidence and prevalence of comorbidity in multiple sclerosis: Overview (2015, neutral): “272 Although we quantified heterogeneity, we did not quantitatively evaluate factors contributing to that heterogeneity due to inconsistent reporting across studies.”
Effects of Game-Based Learning on Students’ Critical Thinking: A Meta-Analysis (2021, methodology): “…publication bias if (a) variability among studies yields effects far from the overall mean or (b) a priori power calculations create an inverse rela- tionship between sample size and efficacy; so we use selection modelling to adjust for publication bias, if needed (Terrin et al., 2003).”
The trim-and-fill method for publication bias: practical guidelines and recommendations based on a large database of meta-analyses (2019, methodology): “, selection models) may be used to better model publication bias in such cases.([22]) Third, meta-analysts should be aware of the potential issues when performing the trim-and-fill method.”
Clinical risk factors for pre-eclampsia determined in early pregnancy: systematic review and meta-analysis of large cohort studies (2016, background): “It can, however, be difficult to assess publication bias when effect sizes are highly heterogeneous, 119 as was the case here.”
Contour-enhanced meta-analysis funnel plots help distinguish publication bias from other causes of asymmetry. (2008, methodology): “Trim and fill is an iterative nonparametric method used to investigate the number of ‘‘missing’’ studies in a meta-analysis due to funnel plot asymmetry and offers an ‘‘adjusted’’ pooled estimate as a sensitivity analysis: its ability to detect publication bias has been found to be variable [14,16,1”
Comparative Effectiveness of Technology-Enhanced Simulation Versus Other Instructional Methods: A Systematic Review and Meta-Analysis (2012, neutral): “Study design (maximum, 3) Observational 2-group design (2) 21 (23)”
How Many Scientists Fabricate and Falsify Research? A Systematic Review and Meta-Analysis of Survey Data (2009, methodology): “The popular funnel-plot-based methods to test for publication bias in meta-analysis are inappropriate and potentially misleading when the number of included studies is small and heterogeneity is large [25], [26].”
Computerized Virtual Patients in Health Professions Education: A Systematic Review and Meta-Analysis (2010, methodology): “40 We used SAS 9.1 (SAS Institute, Cary, North Carolina) to calculate ICC.”
Quantifying Publication Bias in Meta-Analysis (2017, methodology): “…bias tests have been widely used in meta-analysis applications, they may suffer from inflated type I error rate or poor power in certain simulation settings (Sterne et al., 2000; Terrin et al., 2003; Peters © 2017, The International Biometric Society 785 et al., 2006, 2007; Rücker et al., 2008).”