[R-meta] Outlier and influential case diagnostics using generalized linear mixed models approach
@c @end|ng |rom |mb|@un|-|re|burg@de
Mon Mar 2 20:16:25 CET 2020
Am 17.02.20 um 16:14 schrieb Joao Afonso:
> Dear all,
> I am developing a generalized linear mixed model for my meta-analysis
> on lameness prevalence in British Dairy Cattle. Everything seems to be
> working fine however when I try to identify outlier using functions
> rstudent, leave1out and influence R informs that "no applicable method
> ... applied to an object of class "c('metaprop', 'meta')". Is there a
> way to do the diagnostic of influential cases with a rma.glmm object?
The leave-one-out method is available in metainf() of *meta*.
For regression diagnostics provided by *metafor*, you have to conduct a
meta-regression of your subgroup meta-analysis first.
m = metaprop(nlameanimal, ssizeanimal, author, data=prevalence_2020_noout,
method="inverse", sm="PLOGIT", method.tau="DL",
byvar=lcmbi, tau.common=TRUE,prediction = TRUE)
mr = metareg(m)
Best wishes, Guido
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