Figure 1. A. Funnel plot of observed and imputed studies of Impact of alcohol consumption on COVID-19 severity.
Large studies appear toward the top of the graph and tend to cluster near the mean effect size. Smaller studies appear toward the bottom of the graph, and (since there is more sampling variation in effect size estimates in the smaller studies) will be dispersed across a range of values. In the absence of publication bias we would expect the studies to be distributed symmetrically about the combined effect size. By contrast, in the presence of bias, we would expect that the bottom of the plot would show a higher concentration of studies on one side of the mean than the other. This would reflect the fact that smaller studies (which appear toward the bottom) are more likely to be published if they have larger than average effects, which makes them more likely to meet the criterion for statistical significance. These figures represent unlikely or no bias between the included studies concerning Impact of alcohol consumption on COVID-19 severity. Each plot represents an individual cohort or study and this plot has been constructed using CMA software (Version 3.3.070) USA.