simsem (version 0.5-16)

plotCutoffNested: Plot sampling distributions of the differences in fit indices between nested models with fit indices cutoffs

Description

This function will plot sampling distributions of the differences in fit indices between nested models if the nested model is true. The users may add cutoffs by specifying the alpha level.

Usage

plotCutoffNested(nested, parent, alpha = 0.05, cutoff = NULL, 
usedFit = NULL, useContour = T)

Arguments

nested

'>SimResult that saves the analysis results of nested model from multiple replications

parent

'>SimResult that saves the analysis results of parent model from multiple replications

alpha

A priori alpha level

cutoff

A priori cutoffs for fit indices, saved in a vector

usedFit

Vector of names of fit indices that researchers wish to plot the sampling distribution.

useContour

If there are two of sample size, percent completely at random, and percent missing at random are varying, the plotCutoff function will provide 3D graph. Contour graph is a default. However, if this is specified as FALSE, perspective plot is used.

Value

NONE. Only plot the fit indices distributions.

See Also

• '>SimResult for simResult that used in this function.

• getCutoffNested to find the difference in fit indices cutoffs

Examples

# NOT RUN {
# Nested model: One factor
loading.null <- matrix(0, 6, 1)
loading.null[1:6, 1] <- NA
LY.NULL <- bind(loading.null, 0.7)
RPS.NULL <- binds(diag(1))
RTE <- binds(diag(6))
CFA.Model.NULL <- model(LY = LY.NULL, RPS = RPS.NULL, RTE = RTE, modelType="CFA")

# Parent model: two factors
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) 
Output.NULL.ALT <- sim(10, n=500, model=CFA.Model.ALT, generate=CFA.Model.NULL)

# Plot the cutoffs in nested model comparison
plotCutoffNested(Output.NULL.NULL, Output.NULL.ALT, alpha=0.05)
# }