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English
Etymology
From meta- + bias.
Noun
metabias (plural metabiases)
- A biasing factor, such as publication bias, that results in the available data becoming artificially skewed.
2010, John R. Woodward, Nottingham, “The Necessity of Meta Bias in Search Algorithms”, in International Conference on Computational Intelligence and Software Engineering (CiSE), number Dec., IEEE, →DOI, page 2b:An algorithm needs some method of altering its base bias as it is presented with sets of instances. The major claim of this paper is that, as the vast majority of algorithms are intended for use on a collection of problem instances, that meta bias is therefore necessary. Evidence for the fact that algorithms are intended to be reused is that the proponents of newly proposed algorithm test them on a number of problem instances which are reported in their papers. Meta bias is any mechanism which can adjust the base bias (see figure 2 i.e. it is a probability distribution over a set of base biases).
2012, AJ Nordmann, B Kasenda, M Briel, “Meta-analyses: what they can and cannot do”, in Swiss medical weekly:One of the most important metabiases is reporting bias. Only about 50% of randomised trials ultimately reach publication in a journal indexed in a major electronic database
2017, FR Schroeck, BL Jacobs, SB Bhayani, PL Nguyen, D Penson, J Hu, “Cost of New Technologies in Prostate Cancer Treatment: Systematic Review of Costs and Cost Effectiveness of Robotic-assisted Laparoscopic Prostatectomy, Intensity-modulated Radiotherapy, and Proton Beam Therapy”, in European urology, Elsevier:Given the topic of this review, formal assessment of metabiases such as publication bias or selective reporting within studies was not feasible.
2020 March 19, Derek S. Chew, Eric Black-Maier, Zak Loring, Peter A. Noseworthy, Douglas L. Packer, Derek V. Exner, Daniel B. Mark, Jonathan P. Piccini, “Diagnosis-to-Ablation Time and Recurrence of Atrial Fibrillation Following Catheter Ablation. A Systematic Review and Meta-Analysis of Observational Studies”, in Arrhythmia and Electrophysiology, number 13:e008128, →DOI:Heterogeneity across the studies was tested with the Cochran Q and I2 statistics. We considered an I2 statistic of >25% as a low degree of heterogeneity, >50% as moderate heterogeneity, and >75% as high heterogeneity. To ascertain potential meta-bias, a funnel plot was qualitatively assessed for asymmetry.
2021, Desai S, Mehta KM, Singh RJ, et al., “Effects of integrated economic and health interventions with women’s groups on health-related knowledge, behaviours and outcomes in low-income and middle-income countries: a systematic review protocol.”, in BMJ Open:Metabiases / We will plot study sample size against effect size to evaluate whether these are skewed and asymmetrical in the presence of publication bias and other biases. In addition, the risk of bias assessment tools will identify whether studies indicate selective reporting of outcomes, which we will summarise across studies if possible.
Hyponyms
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