OpenMx (version 2.7.9)

omxRMSEA: Get the RMSEA with confidence intervals from model

Description

This function calculates the Root Mean Square Error of the Approximation (RMSEA) for a model and computes confidence intervals for that fit statistic.

Usage

omxRMSEA(model, lower=.025, upper=.975, null=.05, ...)

Arguments

model

An MxModel object for which the RMSEA is desried

lower

The lower confidence bound for the confidence interval

upper

The upper confidence bound for the confidence interval

null

Value of RMSEA used to test for close fit

...

Further named arguments passed to summary

Value

A named vector with elements lower, est.rmsea, upper, null, and `Prob(x <= null)`.

Details

To help users obtain fit statistics related to the RMSEA, this function confidence intervals and a test for close fit. The user determines how close the fit is required to be by setting the null argument to the value desired for comparison.

References

Browne, M. W. & Cudeck, R. (1992). Alternative Ways of Assessing Model Fit. Sociological Methods and Research, 21, 230-258.

Examples

require(OpenMx)
data(demoOneFactor)
manifests <- names(demoOneFactor)
latents <- c("G")
factorModel <- mxModel("One Factor", 
                       type="RAM",
                       manifestVars=manifests, 
                       latentVars=latents,
                       mxPath(from=latents, to=manifests),
                       mxPath(from=manifests, arrows=2),
                       mxPath(from=latents, arrows=2, free=FALSE, values=1.0),
                       mxData(observed=cov(demoOneFactor), type="cov", numObs=500))
factorRun <- mxRun(factorModel)
factorSat <- mxRefModels(factorRun, run=TRUE)
summary(factorRun, refModels=factorSat)
# Gives RMSEA with 95% confidence interval

omxRMSEA(factorRun, .05, .95, refModels=factorSat)
# Gives RMSEA with 90% confidence interval
#  and probability of 'close enough' fit