-----Original Message-----
From: Rafael Rios Moura [mailto:biorafaelrm at gmail.com]
Sent: Wednesday, 09 December, 2020 19:00
To: Viechtbauer, Wolfgang (SP)
Cc: r-sig-meta-analysis at r-project.org
Subject: Re: Extracting residuals from rma.mv function
Dear Wolfgang,
Thank you very much for the reply. I tried to add standard errors as a fixed
predictor in the repeatability test, but I obtained these errors:
Warning messages:
1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,:
unable to evaluate scaled gradient
2: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,:
Problem with Hessian check (infinite or missing values?)
I used an optimizer, but It did not work. I do not know exactly if I need to
account for standard errors in the repeatability test. It seems that the
residuals are enough, but I would be grateful if you can share with me your
thoughts about it. I ran a random-effects multilevel meta-analysis using
effect size ID, study ID, species ID, and phylogenetic correlations as
random effects. Then, I extracted standard residuals to use as a response
variable in the repeatability test using rptR package. The test is a general
linear mixed model which measures the among-group variance attributed to a
particular random variable (corresponding to spatial replicates, for
example) divided by the sum of the?within-group residual variance and the
among-group variance to calculate a R statistic. rpt function of rptR
package also performs bootstrapping methods to calculate confidence
intervals and P-values. Do you think that I need to include another variable
within the repeatability model? Thank you in advance.
Stoffel et al. 2007:
https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/2041-
210X.12797%4010.1111/%28ISSN%292041-210X.CODEVI2018
All the best,