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A funnel plot is a scatterplot of treatment effect against a measure of study precision. It is used primarily as a visual aid for detecting bias or systematic heterogeneity. A symmetric inverted funnel shape arises from a ‘well-behaved’ data set, in which publication bias is unlikely. An asymmetric funnel indicates a relationship between ...
Funnel plot of a meta-analysis of stereotype threat on girls' math scores showing asymmetry typical of publication bias. From Flore, P. C., & Wicherts, J. M. (2015) [17] There is extensive meta-research on publication bias in the biomedical field. Investigators following clinical trials from the submission of their protocols to ethics ...
Funnel plot : This is a useful graph designed to check the existence of publication bias in meta-analyses. Funnel plots, introduced by Light and Pillemer in 1994 [6] and discussed in detail by Egger and colleagues, [7] are useful adjuncts to meta-analyses. A funnel plot is a scatterplot of treatment
The problem of publication bias is not trivial as it is suggested that 25% of meta-analyses in the psychological sciences may have suffered from publication bias. [120] However, low power of existing tests and problems with the visual appearance of the funnel plot remain an issue, and estimates of publication bias may remain lower than what ...
Publication bias – which can be detected with a funnel plot – leads to overrepresentation of studies that report a correlation or large effect size. Daryl Bem's claimed evidence of effect preceding cause is used as an example.
Meta Analysis: Synthesise evidence across multiple studies. Includes techniques for fixed and random effects analysis, fixed and mixed effects meta-regression, forest and funnel plots, tests for funnel plot asymmetry, trim-and-fill and fail-safe N analysis. Network: Explore the connections between variables organised as a network. Network ...
[1] [8] Like publication bias, the existence of researcher degrees of freedom has the potential to lead to an inflated degree of funnel plot asymmetry. [9] It is also a potential explanation for p-hacking, as researchers have so many degrees of freedom to draw on, especially in the social and behavioral sciences.
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