Which of the several measures of d-statistics is better for a meta-analysis of effect-sizes? Several measures including Cohen's d are available for computing d-statistics. It is difficult to choose one of them for a meta-analysis? Are there any guidelines ?
 A: In his book, Card (2012) covers three of the common standardized mean difference measures: Cohen's $d$, Hedge's $g$, and Glass's $\Delta$. The three differ with respect to the calculation of their denominators:


*

*$d$ uses the pooled sample standard deviations as the denominator

*$g$ uses the pooled estimated population standard deviations as the denominator

*$\Delta$ uses the estimated population standard deviation of one group, usually from a "control" group in the context of an experimental intervention-based study.


Short Answer:
In many, perhaps even most cases, you will probably want to use g, though in some specific cases, $\Delta$ will be the way to go.
Long Answer:
Card (2012) goes on to say that $d$'s denominator underestimates the pooled standard deviation, particularly in smaller samples, such that $g$ is preferable. Though in many cases with larger sample sizes, $d$ and $g$ will yield virtually identical estimates of effect size. 
Whether $g$ is preferable to $\Delta$ depends on whether you think the population standard deviations of the two groups being compared are homogenous or heterogenous. If you think they are homogenous, Card recommends using $g$, and not $\Delta$, as $g$ takes information from both groups into consideration when estimating the pooled standard deviation. However, if you think the population standard deviations of the two groups are heterogenous, then using $\Delta$ may be more advisable measure. However, a further complication of using $\Delta$ is that it is not computable unless articles report the standard deviations of each group (so that you can extract the one from the group that you wish to use to compute $\Delta$).  
References
Card, N. A. (2012). Applied meta-analysis for social science research. New York, NY: Guilford Press.
