[R-meta] Subgroup analysis output using metafor - interpretation

[Joao Afonso]

Dear all,

I am running a meta-analysis on the prevalence of lameness (binary) in
British dairy cattle and have used the *metaprop* from the *metafor* package.
I have set the model to run with random effects, using the DL method, and
have taken the following approach:

   1. log-transform the data as it is not normally distributed
   2. identify outliers using influential analysis (only ran this once)
   3. remove outliers and rerun the model
   4. deal with remaining heterogeneity with subgroup analysis and
   meta-regression

I have ran the model and am getting what I believe conflicting evidences on
different output indicators. As an example, after running subgroup analysis
with one moderator, the output tells me that the moderator explains around
50% of the heterogeneity (R^2), and yet the p-value for the test of
moderators is substantially higher than 0.05 telling me that the pooled
estimates of the subgroups aren't actually different.



I was hoping you could shed a light as to what could justify this happening
(if it makes sense), and possibly provide some guidance as to what I could
do to improve the statistical evidences of my study.


Many thanks and happy 2020 to everyone

-- 
João Afonso
*DVM, MSc Veterinary Epidemiology*
*PhD Student *
*Department of Infection and Global Health*
*University of Liverpool*
*+351914812305*

	[[alternative HTML version deleted]]