HS.model <- ' visual =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed =~ x7 + x8 + x9 '
fit <- cfa(HS.model, data=HolzingerSwineford1939)
# extract partable (only first six columns are needed)
partable <- parTable(fit)[,1:6]
# add matrix representation
lavMatrixRepresentation(partable)
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