Despite being able to derive meta-analytic estimates from a large number of administrations of six repeated national surveys, there are several limitations to these findings. The first is the assumption of the random-effects meta-analysis model: that the trend estimates from the surveys are drawn from a theoretical normally distributed sample. In other words, differences between estimates constitute random error rather than bias. It may be that some surveys are inherently better at measuring alcohol-related behaviors than others, or that some surveys are more methodologically consistent from year to year than others. Perhaps ideally, some surveys should be weighted more highly than the others. The agnostic meta-analytic approach may not be optimal, but our results underscore the importance of synthesizing data from multiple sources. Relatedly, we emphasize that this analysis of relative change in outcomes over time does not help clarify differences among point-prevalence estimates. The random-effects model assumes all prevalence estimates are influenced by unobservable factors that are specific to each survey. Additionally, we noted that some surveys changed the threshold for women in binge drinking questions, and that the
