[R-meta] Co-variances of the random structure
Gram, Gil (IITA)
G@Gr@m @end|ng |rom cg|@r@org
Tue Feb 18 12:12:34 CET 2020
Dear all,
I have the following question: is it possible to extract the covariances from random variance components of a rma.mv model? For example, from my model below this email.
Thanks in advance you for your help,
Gil
---
My model design:
MOD = rma.mv(sqrt(yi), vi, method = 'REML', struct="HCS", sparse=TRUE, data=dat,
mods = ~ rateORone + rateORtwo + rateORthree + rateORManure + kgMN
+ I(rateORone^2) + I(rateORtwo^2) + I(rateORthree^2) + I(rateORManure^2) + I(kgMN^2)
+ rateORone:kgMN + rateORtwo:kgMN + rateORthree:kgMN + rateORManure:kgMN
+ I(rateORone^2):I(kgMN^2) + I(rateORtwo^2):I(kgMN^2) + I(rateORthree^2):I(kgMN^2) + I(rateORManure^2):I(kgMN^2)
+ cropSys + idF,
random = list(~1|ref, ~1|idRow, ~ treatment|idSite, ~ treatment|idSite.time))
Where ‘treatment’ in the random structure has 4 levels, Control, OR, MR and ORMR.
I wish to evaluate the variances of the responses of the 3 last levels with the first. For instance with OR: Var_response = Var_OR + Var_control – 2 * Cov_OR:control.
My model output yields the following:
Multivariate Meta-Analysis Model (k = 2695; method: REML)
Variance Components:
estim sqrt nlvls fixed factor
sigma^2.1 0.0513 0.2264 34 no ref
sigma^2.2 0.0139 0.1178 2625 no idRow
outer factor: idSite (nlvls = 62)
inner factor: treatment (nlvls = 4)
estim sqrt k.lvl fixed level
tau^2.1 0.1683 0.4103 255 no Control
tau^2.2 0.1403 0.3745 324 no MR
tau^2.3 0.1305 0.3612 993 no OR
tau^2.4 0.1094 0.3308 1123 no ORMR
rho 0.8343 no
outer factor: idSite.time (nlvls = 230)
inner factor: treatment (nlvls = 4)
estim sqrt k.lvl fixed level
gamma^2.1 0.1061 0.3258 255 no Control
gamma^2.2 0.1272 0.3566 324 no MR
gamma^2.3 0.1052 0.3243 993 no OR
gamma^2.4 0.1344 0.3666 1123 no ORMR
phi 0.9229 no
Test for Residual Heterogeneity:
QE(df = 2673) = 115058.0204, p-val < .0001
Test of Moderators (coefficients 2:22):
QM(df = 21) = 754.8078, p-val < .0001
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