[R-meta] Error: Ratio of largest to smallest sampling variance extremely large

florencia miguel 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
rma.mv functions:
"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 %>%
  filter(intervention=="vegetation") %>%
  filter(!is.na(lrr)) %>%

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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