getCutoffNested {simsem}

Find fit indices cutoff for nested model comparison given a priori alpha level

Description

Extract fit indices information from the simulation of parent and nested models and getCutoff of fit indices given a priori alpha level

Usage

getCutoffNested(nested, parent, alpha = 0.05, usedFit = NULL, nVal = NULL, 
	pmMCARval = NULL, pmMARval = NULL, df = 0)

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

usedFit

Vector of names of fit indices that researchers wish to getCutoffs from. The default is to getCutoffs of all fit indices.

nVal

The sample size value that researchers wish to find the fit indices cutoffs from.

pmMCARval

The percent missing completely at random value that researchers wish to find the fit indices cutoffs from.

pmMARval

The percent missing at random value that researchers wish to find the fit indices cutoffs from.

df

The degree of freedom used in spline method in predicting the fit indices by the predictors. If df is 0, the spline method will not be applied.

Value

One-tailed cutoffs of several fit indices with a priori alpha level

Author(s)

Sunthud Pornprasertmanit ([e-mail])

See Also

SimResult for a detail of simResult getCutoff for a detail of finding cutoffs for absolute fit

Examples

## 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)

## End(Not run)