[R-meta] Accounting for sources of variation in meta-analysis
Carla Gomez Creutzberg
cgomezcre at gmail.com
Mon Mar 19 04:53:02 CET 2018
Dear fellow meta-analysts:
I hope this message finds you all well.
I have collected information on the provision of ecosystem services by
different land uses and have conducted a meta- analysis on this. However, I
now wish to expand this analysis to a subset of our meta-dataset that,
besides the effect of different land uses on ecosystem service provision,
also has data on the biodiversity of each land use. I would like to use
this to explore if biodiversity accounts for some (or all) of the effect we
see of land use on ecosystem service provision.
After reading a bit, I am beginning to think that one of the ways that we
could probably use to approach this analysis would be a long the lines of
MASEM (Meta-analytic structural equation modelling) or a structural
equation modelling -based meta-analysis. I am entirely sure yet which one
applies best to our case yet but probably its the second one, which seems
to be not so well documented. In any case, at this stage, both options seem
a bit intimidating and complex so I was wondering if anybody knew of any
alternative methods to separate the effect of land use and biodiversity in
the provision of ecosystem services within our datset? I am not sure if
taking biodiversity as a moderator would be of any help with this? In our
dataset, for each study, we have information on 2 or more land uses, and
for each land use we have an indicator of ecosystem service provision and
an indicator biodiversity.
What ultimately interests us is the effect of land use on ecosystem
services with and without accounting for biodiversity. However, I am
concerned that to tease this apart we may need to eventually have
biodiversity as a response to land use and ecosystem services as a response
to land use as well which could give rise to problems with non-independence
since we would have 2 effect sizes per study.
Any insights or suggestions on this are certainly most welcome.
Thanks for you attention!
*Carla Gómez Creutzberg*
PhD. Candidate - Tylianakis Lab
University of Canterbury - *Te Whare Wānanga o Waitaha*
Christchurch, New Zealand
cgomezcre at gmail.com
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