Has the Time Come to Stop Using the "Standardised Mean Difference"?

Most meta-analyses use the 'standardised mean difference' (effect size) to summarise the outcomes of studies. However, the effect size has important limitations that need to be considered.

After a brief explanation of the standardized mean difference, limitations are discussed and possible solutions in the context of meta-analyses are suggested.

When using the effect size, three major limitations have to be considered. First, the effect size is still a statistical concept and small effect sizes may have considerable clinical meaning while large effect sizes may not. Second, specific assumptions of the effect size may not be correct. Third, and most importantly, it is very difficult to explain what the meaning of the effect size is to non-researchers. As possible solutions, the use of the 'binomial effect size display' and the number-needed-to-treat are discussed. Furthermore, I suggest the use of binary outcomes, which are often easier to understand. However, it is not clear what the best binary outcome is for continuous outcomes.

The effect size is still useful, as long as the limitations are understood and also binary outcomes are given.