[R-meta] Error: Ratio of largest to smallest sampling variance extremely large
m||orm|gue| @end|ng |rom gm@||@com
Thu Feb 14 20:52:11 CET 2019
Dear all, I am running a meta analysis with the main aim of comparing three
different kind of interventions and four kind of outcomes. I want to
perform different models for interventions and outcomes. I could run random
effects models using the package meta but, as I need to include moderators
in the models I tryed the metafor package.
The problem is that I obtained this error when running rma.uni and
"Error in rma.mv(yi = lrr, V = var.es, mods = ~aridity.index, method =
"REML", : Ratio of largest to smallest sampling variance extremely large.
Cannot obtain stable results."
I am using Log response ratio as effect sizes. I know that data are very
heterogeneous (some rows with high variances values and other with low
variances) because I am comparing different kind of measures. So, I
performed models by subgroups (subsetting by interventions), and I obtained
the same type of error.
Here are some codes:
mod1 <- rma(lrr, var.es, mods= aridity.index, data=mdata.all,
mod.2<-rma.mv(yi=lrr, V=var.es, mods= aridity.index, method = "REML",
test="t", random = ~ 1 | ID, data=mdata.all, sparse=TRUE)
mod.3 <- rma(lrr, var.es, mods= ~intervention, data = mdata.all, subset =
paradigm == "active")
##filtering by interventions
mdata.veg <- mydata %>%
mod<-rma(lrr,var.es, mods= aridity.index, digits=4,data=mdata.veg)
I dont know why i getting the same error after subsetting or filtering by
Thank you in advance!
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