The background is a forest plot of a meta-analysis which is reported to have been calculated with a "random effects model". The pooled effect is reported as a standardized mean difference (SMD).
Results below the forest plot are listed to have:
Heterogeneity: I-squared=94%, tau-squared=0,11, p<0,0002
Regarding the reporting of heterogeneity:
- a) What is the practical value of the reported heterogeneity in regard to the interpretation of the results of a meta-analysis? (In my understanding it shows the differences of the included study results in relation to the overall results)
- b) Is there, for example, a certain "threshold percentage" when results should not be considered as reliable or meta-analyis should not be undertaken at all?
Regarding the reported significance (p<0,0002)
- a) Does it refer to the heterogeneity results or the pooled effect results of the overall forest plot? (In my understanding it refers only to the heterogeneity results.)
- b) What is the practical value of the reported significance in regard to interpretation? (Does it somehow show the validity or robustness of the heterogeneity results?)
The question is asked from a beginners perspective in statistics.
More background information: the metaanalysis was done with six different studies, also using different outcome measures. No subgroup analysis was possible because of heterogeneity. Meta-regression ist also not advisable when there are less than 10 studies, according to the Cochrane foundation http://handbook.cochrane.org/chapter_9/9_6_4_meta_regression.htm