In random-effects meta-analysis, the extent of variation among the effects observed in different studies (between-study variance) is referred to as tau-squared, τ^{2}, or Tau^{2} (Deeks et al 2008). τ^{2} is the variance of the effect size parameters across the population of studies and it reflects the variance of the true effect sizes. The square root of this number is referred to as tau (T). T^{2} and Tau reflect the amount of true heterogeneity. T^{2} represents the absolute value of the true variance (heterogeneity). T^{2} is the variance of the true effects while tau (T) is the estimated standard deviation of underlying true effects across studies (Deeks et al 2008). The summary meta-analysis effect and T as standard deviation may be reported in random-effects meta-analysis to describe the distribution of true effects (Borenstein et al 2009).