[R-meta] Inconsistency Testing
@e@n@toporek @end|ng |rom gm@||@com
Tue Mar 9 23:22:12 CET 2021
I’ve been stuck on a question about inconsistency testing for quite
some time, but first a little simplified background:
I’ve calculated effect sizes for all treatments from 50 independent
trials conducted over the past 10 years. These treatments are
different fungicides applied to a plant to control a foliar pathogen.
Throughout those 10 years, researchers tested 20 different products,
and a treatment (4-15 per trial) is different combinations of usually
1-6 of those fungicides. There was no coordination over those 10 years
in experimental design, so no treatment was truly replicated. Instead,
what I’ve done is reduce treatments into larger categories based on
the modes of action of those fungicides. This has allowed me to have
enough similarly coded treatments to perform a network meta-analysis.
That went all well and good, however, when it comes to inconsistency
testing, I have as many study designs as I have studies. 50
independent trials, 50 designs.
Can I even technically perform inconsistency testing? What I've read
in the literature doesn't seem to account for my situation. If not,
what does this mean for my meta-analysis? Do I truly need to perform
Thank you all for your time, hope your week is going well!
More information about the R-sig-meta-analysis