[R-sig-ME] One model of two subsets of data

[Timothy MacKenzie]

Hello All,

I have two questions:

First, I was wondering if "model_2" (even subset of items in model_1)
and "model_3" (odd subset of items in model_1) results (fixed and
random) can be derived from model_1?

Second, from "model_2" and "model_3", suppose I draw the `Subject`
random effects and correlate them:

ranef_model_2_even = data.frame(ranef(model_2)$Subject)
ranef_model_2_even$Subject <- row.names(ranef_model_2_even)
ranef_model_3_odd = data.frame(ranef(model_3)$Subject)
ranef_model_3_odd$Subject <- row.names(ranef_model_3_odd)

Subject = merge(ranef_model_2_even, ranef_model_3_odd, by = "Subject",
suffixes = c("_even", "_odd"))
cor(Subject$Conditionunrelated_even, Subject $Conditionunrelated_odd)
#  [1] 0.849635


**** Could we obtain the latent equivalent of the above correlation
(which may not be numerically the same as 0.849635) from
`VarCorr(model_1)`?

Thank you all, Tim M

## Reproducible data and code:
d = read.csv("https://raw.githubusercontent.com/fpqq/w/main/d3.csv")
library(optimx)
library(blme)

model_1 = blmer(I(-1/RT) ~ Condition:item_num +
(Condition:item_num|Subject) + (Condition:item_num|Item), data = d,
             control=lmerControl(optimizer="optimx",optCtrl=list(method="nlminb")))

# Subset 1:
model_2 = blmer(I(-1/RT) ~ Condition + (Condition|Subject) + (Condition|Item),
data = d, control=lmerControl(optimizer="optimx",optCtrl=list(method="nlminb")),
           subset = item_num == "Even")

# Subset 2:
model_3 = blmer(I(-1/RT) ~ Condition + (Condition|Subject) + (Condition|Item),
data = d, control=lmerControl(optimizer="optimx",optCtrl=list(method="nlminb")),
             subset = item_num == "Odd")