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.