The median is very similar to the mean when the distribution of the data is symmetrical, and so occasionally can be used directly in meta-analyses. However, means and medians can be very different from each other if the data are skewed, and medians are often reported because the data are skewed (see Chapter 9, Section 9.4.5.3).
Interquartile ranges describe where the central 50% of participants’ outcomes lie. When sample sizes are large and the distribution of the outcome is similar to the normal distribution, the width of the interquartile range will be approximately 1.35 standard deviations. In other situations, and especially when the outcomes distribution is skewed, it is not possible to estimate a standard deviation from an interquartile range. Note that the use of interquartile ranges rather than standard deviations can often be taken as an indicator that the outcomes distribution is skewed.