Test for Subgroup Difference Compared to Test for Moderator I have performed a proportional meta-analysis to evaluate the rate of procedural success for two medical procedures. The two procedures comprise the two subgroups in my meta-analysis (FNA and FNB). I am trying to understand whether or not there is a statistically significant difference between the rate of success between my subgroups.
This is the output from the meta-analysis using a REML random effects model, followed by meta-regression. The test for subgroup difference appears to show a statiistically significant difference between the subgroups (based on the common-effects difference for subgroups test), while the test for moderator shows no statistical significance.
Meta-Analysis:

Meta-Regression:

Any insight on how to reconcile these varying outcomes would be much appreciated. I have very minimal statistics background, so please let me know if there is anything I can clarify. Thanks.

The common effects model is a fixed effects model, which gives incorrect estimates and standard errors in the presence of heterogeneity (and you have lots of heterogeneity).
If you run your meta-regression as a fixed effects model, I imagine you'll get the same (incorrect) significant result.
Incidentally, please give us the code that you ran to get this result, and don't paste your code or as an image - it means I can't copy and paste parts of the code or output.
