Table 1


Publication biasThe publication or non-publication of research findings, depending on the nature and direction of the results.22
Certainty in the evidenceThe certainty that a true effect lies on one side of a specified threshold or within a chosen range supporting a decision.4
Selection modelA weight function of effect size or p value is used to model the probability of publication. This method highly depends on this weight and is usually recommended as a sensitivity analysis.
Begg testA method that uses the rank test to examine the association between the observed effect sizes and their variances. However, it suffers from low statistical power.
Egger testA method in which we regress the standardised effect size against the precision. The intercept is close to zero if no publication bias is present. This method may have inflated false-positive rates for ORs.
Trim and fill methodA method in which the missing studies are imputed to provide a bias-adjusted effect estimate. However, it requires the strong assumption that the missing studies have the most negative (or positive) effect sizes.
SkewnessA method that examines the asymmetry of residuals of the regression test. It has more statistical power than other tests. However, it may lose power if the available studies have a distribution that tends to have multiple modes.