I am trying to run multi-level modeling using imputed dataset.
imp <- mice(data, m= 20, method = "pmm")
out1 <- with(data= imp, exp = lmer(issue.atti1 ~ age+gender+race+edu+pre1+pre2+group1+(1|state))
out1.pool <- pool(out1)
summary(out1.pool)
The summary of the pooled output provided fixed effects and intercepts, but not ICC (intra-class correlation) and AIC.
I tried this way:
sapply(out1.pool $analyses, AIC)
But it provides the list of AIC not AIC of pooled results.
#[1] 18229.26 18156.71 18197.92 18180.91 18155.70 18180.63 18190.48 18268.03 18174.94 18131.65
#[11] 18174.40 18172.52 18200.76 18150.48 18156.84 18237.29 18195.19 18241.88 18225.97 18127.35
How could I get the pooled AIC? I don't think we should report all of AIC in the paper.
Also, I have no idea how to get ICC for this pooled model. performance::icc() does not work here.
Does anyone have any solutions?