Globals analysis

This procedure conducts the meta-analysis of the global variables, e.g., the global gray matter in a meta-analysis of VBM studies. You can specify up to 2 indicators to define groups (i.e. for a 3 groups comparison), up to 2 covariates, and up to 1 filter for subgroup analyses. The statistic used is the unbiased Hedge's d, and the meta-analysis is conducted using the restricted maximum-likelihood (i.e. the default method in the previously available MiMa S-Plus/R function by Wolfgang Viechtbauer).

Notes

Before conduting this analysis, the following variables must be created in the SDM table:

- In one sample studies (e.g., studies investigating the brain response to fearful faces in healthy volunteers): n1 (sample size), mean1 (mean of the global variable of interest) and sd1 (standard deviation of the global variable of interest).

- In two samples studies (e.g., studies comparing the gray matter volume in patients vs. healthy controls): n1 and n2 (sizes of the two samples), mean1 and mean2 (means of the variable of interest, e.g., global gray matter), and sd1 and sd2 (standard deviations of the variable of interest).

If one variable is selected in the dialog (e.g., a filter for subgroup comparison or a covariate), '0' estimates the global value at the minimum value of the variable, '1' estimates the global value at the maximum value of the variable, and '1m0' estimates the difference in global value between the maximum and the minimum values of the variable. If two variables are selected, '10' relates to the maximum value of the first variable and the minimum of the second, while '01' relates to the minimum value of the first variable and the maximum of the second. And so on...

If two variables are selected, the two-variable Q is also computed, with a meaning similar to the F of an ANOVA.

To conduct a globals analysis:

Press the button [Globals]

or:

Select [Globals] in the Statistics menu.

Command-line and batch usage

globals formula, filter

Example:

GGM = globals

References

Hedges LV, Olkin I. Statistical Methods for Meta-Analysis. Orlando: Academic Press; 1985.