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[5] Rosenthals fail-safe number or fail-safe N method is another way of determining publication bias. [6] It identifies the number of additional negative studies to increase the P value in a meta-analysis to above 0.05. Although it a simple way of deriving a number, it is dependent on P value.
The three stages at which bias can be injected into a meta-analysis are finding studies, selection of the identified studies for the meta-analysis and extraction of data from the selected studies.
The funnel plot is widely and frequently used in meta-analyses for assessing publication bias; it is a scatter plot with studies effect sizes on the horizontal axis and their standard errors (or other measures of precision, e.g., sample sizes) on the vertical axis.
Eggers test is commonly used to assess potential publication bias in a meta-analysis via funnel plot asymmetry (Eggers test is a linear regression of the intervention effect estimates on their standard errors weighted by their inverse variance).
Eggers test is commonly used to assess potential publication bias in a meta-analysis via funnel plot asymmetry (Eggers test is a linear regression of the intervention effect estimates on their standard errors weighted by their inverse variance).
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The estimated value of the intercept in Egger regression ^ 0 E can be interpreted as an estimate of the average pleiotropic effect across the genetic variants. An intercept term that differs from zero is indicative of overall directional pleiotropy.
How do you handle publication bias in your meta-analysis? Assess the risk of publication bias. Use funnel plots and tests. Use trim and fill methods. Use sensitivity analyses. Use alternative methods. Heres what else to consider.
A funnel plot can visually reveal the presence of a publication bias. A funnel plot is a graphic representation in which the size of the study on the y axis is plotted against the measure of effect on the x axis.

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