mem_w@|ton @end|ng |rom y@hoo@co@uk
Fri Mar 10 12:46:49 CET 2023
I wonder if some one can help.
I am using metamean to determine with of my habitats have the most microplastics, I have collected 400+ papers with means, SD and sample number.Using the command:-metamean(MP_global, mean=meanMP_per_m2, na.rm=TRUE, sd=MP_SD, na.rm=TRUE,n=Sample_no, na.rm=TRUE ,byvar=Ecosystem, na.rm=TRUE,comb.random=TRUE,comb.fixed=FALSE,verbose=TRUE, control=list(maxiter=1000))
I get some repeated warnings: Warning: Studies with non-positive standard deviation get no weight in meta-analysis.Warning: Ratio of largest to smallest sampling variance extremely large. May not be able to obtain stable results.
But the model converges and I get means and confidence intervals, and significant differences between subgroups
However when I estimate my own mean values for each habitat weighted by sample number (below) the values are very different for some, and I am worried that the metamean results are not a true reflection of the data.
ddply(MP_global, .(Ecosystem), function(x) data.frame(wret=weighted.mean(x$meanMP_per_m2, x$Sample_no)))
Can anyone shed some light? Is it because metamean is ignoring some values?
Thanks very muchMark
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