library(MIIVmsem)
# read in the data
dat <- read.table("C:/Users/mgiordan/Google Drive/PSYC/RESEARCH/dissertation/programming/miivmsem/tests/famIQData.dat")
names(dat) <- c("fam", "id", paste0("y", 1:6))
model <- "
Level: 1
l1w =~ y1 + y2 + y3
l2w =~ y4 + y5 + y6
l1w ~~ l2w
Level: 2
l1b =~ y1 + y2 + y3
l2b =~ y4 + y5 + y6
l1b ~~ l2b
"
fit <- MsemMiive(model_2lvl = model,
data = dat,
cluster = "fam",
printProg = TRUE)
parameterEstimatesTable(fit)
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