R: Assign Model Parameters

mxCompare {OpenMx}

R Documentation

Assign Model Parameters

Description

Compare the fit of one or more models to a base model. The output is a table with one row per model comparison.

Usage

mxCompare(base, comparison, ..., all = FALSE)

Arguments

`base`	A MxModel object or list of MxModel objects.
`comparison`	A MxModel object or list of MxModel objects.
`...`	Not used. Forces remaining arguments to be specified by name.
`all`	A boolean value on whether to compare all bases with all comparisons.

Details

Use options('digits' = N) to set the minimum number of significant digits to be printed in values. The following columns appear in the output:

base: Name of the base model
comparison: Name of the comparison model
ep: Estimated parameters of the comparison model
minus2LL: Minus 2*log-likelihood of the comparison model
df: Degrees in freedom of the comparison model
AIC: Akaike's Information Criterion for the comparison model
diffLL: Change in minus 2*log-likelihood
diffdf: Change in degrees of freedom
p: Significance level of the change in fitness function

Examples


data(demoOneFactor)
manifests <- names(demoOneFactor)
latents <- c("G1")
model1 <- 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(cov(demoOneFactor), type = "cov", numObs = 500)
)

fit1 <- mxRun(model1)

latents <- c("G1", "G2")
model2 <- mxModel(name="Two Factor", type="RAM",
      manifestVars = manifests,
      latentVars = latents,
      mxPath(from = latents[1], to=manifests[1:3]),
      mxPath(from = latents[2], to=manifests[4:5]),
      mxPath(from = manifests, arrows = 2),
      mxPath(from = latents, arrows = 2, free = FALSE, values = 1.0),
      mxData(cov(demoOneFactor), type = "cov", numObs=500)
)
fit2 <- mxRun(model2)

mxCompare(fit1, c(fit2))

# vary precision of the output (no effect for this example)
oldPrecision = as.numeric(options('digits')) 
options('digits' = 3)
mxCompare(fit1, c(fit2))
options('digits' = oldPrecision)