In meta-analysis, the usual way of assessing whether a set of single studies is homogeneous is by means of the Q test. However, the Q test only informs meta-analysts about the presence versus the absence of heterogeneity, but it does not report on the extent of such heterogeneity. Recently, the I[squared] index has been proposed to quantify the degree of heterogeneity in a meta-analysis. In this article, the performances of the Q test and the confidence interval around the I[squared] index are compared by means of a Monte Carlo simulation. The results show the utility of the I[squared] index as a complement to the Q test, although it has the same problems of power with a small number of studies.