[R-meta] Variance inflation factors (VIF) calculations applicable to a rma.mv model

[Martineau, Roger]

Dear list members,

I have the following multilevel model. I want to calculate variance inflation factors (VIF) among Xs to test collinearity.

Does someone know how to get VIF from a rma.mv model ?

> model19 <- rma.mv(MPY, SEM^2, data=dataset,
+                   mods = ~
+                     X1 +
+                     X2 +
+                     X3 +
+                     X4 +
+                     X5,
+                   random = ~ 1|experiment/study/ID,
+                   method = "REML", digits=4)
> robust(model19, cluster= dataset$experiment)

I have this VIF function that I can use for a lmer model (see below) but it doesn’t work for the rma.mv model.

# VIF for lmer model
vif.mer <- function (fit) {
v <- vcov(fit)
nam <- names(fixef(fit))
ns <- sum(1 * (nam == "Intercept" | nam == "(Intercept)"))
if (ns > 0) {
v <- v[-(1:ns), -(1:ns), drop = FALSE]
nam <- nam[-(1:ns)]
}
d <- diag(v)^0.5
v <- diag(solve(v/(d %o% d)))
names(v) <- nam
v
}

Best,

Roger ☺

Roger Martineau, mv Ph.D.
Centre de recherche et de développement
sur le bovin laitier et le porc
Agriculture et agroalimentaire Canada/Agriculture and Agri-Food Canada
Téléphone/Telephone: 819-780-7319
Télécopieur/Facsimile: 819-564-5507
2000, Rue Collège / 2000, College Street
Sherbrooke (Québec)  J1M 0C8
Canada
roger.martineau using agr.gc.ca<mailto:roger.martineau using agr.gc.ca>



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