# NOT RUN {
# Nested Model
loading.null <- matrix(0, 6, 1)
loading.null[1:6, 1] <- NA
LY.NULL <- bind(loading.null, 0.7)
RPS.NULL <- binds(diag(1))
error.cor.mis <- matrix("rnorm(1, 0, 0.1)", 6, 6)
diag(error.cor.mis) <- 1
RTE <- binds(diag(6), misspec=error.cor.mis)
CFA.Model.NULL <- model(LY = LY.NULL, RPS = RPS.NULL, RTE = RTE, modelType="CFA")
# Parent Model
loading.alt <- matrix(0, 6, 2)
loading.alt[1:3, 1] <- NA
loading.alt[4:6, 2] <- NA
LY.ALT <- bind(loading.alt, 0.7)
latent.cor.alt <- matrix(NA, 2, 2)
diag(latent.cor.alt) <- 1
RPS.ALT <- binds(latent.cor.alt, "runif(1, 0.7, 0.9)")
CFA.Model.ALT <- model(LY = LY.ALT, RPS = RPS.ALT, RTE = RTE, modelType="CFA")
# The actual number of replications should be greater than 10.
Output.NULL.NULL <- sim(10, n=500, model=CFA.Model.NULL, generate=CFA.Model.NULL)
Output.NULL.ALT <- sim(10, n=500, model=CFA.Model.ALT, generate=CFA.Model.NULL)
# Find the fix index cutoff from the sampling distribution of the difference
# in fit index of nested models where the alpha is 0.05.
getCutoffNested(Output.NULL.NULL, Output.NULL.ALT, alpha=0.05)
# }
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