At 23:18 11/07/2014, Megan Bartlett wrote:
Hi everyone,
Since metafor doesn't have its own list, I hope this is the correct place
for this posting- my apologies if there is a more appropriate list.
metafor questions welcome here, Megan
Wolfgang seems to be off-list so while we wait for the definitive
answer here are some hints.
I'm conducting a meta-analysis where I would like to determine the
correlation between plasticity in leaf traits and climate. I'm calculating
effect sizes as Hedge's d. My data is structured so that each study
collected data from one forest site, so there is one set of climate
variable values for that study, and there are one or more species in each
study, so all the species in a study have the same values for the climate
variables. I'm not sure how to account for this structure in modeling the
relationship between plasticity and climate.
I think you need rma.mv for your situation and you need to specify a
random effect for site.
Try going
?rma.mv
and looking for the section entitled Specifying random effects
You will need to set up your dataframe with one row per species and
an indicator variable for site and then use
random = ~ 1 | site
Not tested obviously and Wolfgang may have other suggestions
My first thought was to calculate mean effect size and variance across
species for every study with multiple species and correlate that with
the climate variable values for those study with the rma() function, but
trying to do that returns an error message:
rma(yi = EffectSize, vi = Var, data = sitestable, mod = Precip)
returns: Error in wi * (yi - X %*% b)^2 : non-conformable arrays
This leaves me with two questions: 1) Am I even accounting for the data
structure correctly with this approach, and 2) am I fundamentally
misunderstanding how to use metafor to do so?
Thanks very much for your help!
Best,
Megan
[[alternative HTML version deleted]]
Michael Dewey
i...@aghmed.fsnet.co.uk
http://www.aghmed.fsnet.co.uk/home.html
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