Egger's Test evaluates the relationship between the effect size and the standard error of the studies included in a meta-analysis. If there is no publication bias, the effect sizes should be symmetrically distributed around the overall effect size, regardless of the standard error. Egger's Test uses a linear regression approach where the standard normal deviate (effect estimate divided by its standard error) is regressed against the reciprocal of the standard error. A significant intercept suggests asymmetry, indicating potential publication bias.
