Calculate fit measures.
calculateChiSquare(.object)calculateChiSquareDf(.object)
calculateCFI(.object)
calculateGFI(.object, .type = c("ML", "ULS"))
calculateIFI(.object)
calculateNFI(.object)
calculateNNFI(.object)
calculateRMSEA(.object)
calculateRMSTheta(.object)
calculateSRMR(
.object = NULL,
.matrix1 = NULL,
.matrix2 = NULL,
.saturated = FALSE,
...
)
An R object of class cSEMResults resulting from a call to csem()
.
Character string. Which fitting function should the GFI be based on? One of "ML" for the maximum likelihood fitting function or "ULS" for the unweighted least squares fitting function (same as the squared Euclidian distance). Defaults to "ML".
A matrix
to compare.
A matrix
to compare.
Logical. Should a saturated structural model be used?
Defaults to FALSE
.
Ignored.
A single numeric value.
calculateChiSquare
: The chi square statistic.
calculateChiSquareDf
: The ChiSquare statistic divided by its degrees of freedom.
calculateCFI
: The comparative fit index (CFI).
calculateGFI
: The goodness of fit index (GFI).
calculateIFI
: The incremental fit index (IFI).
calculateNFI
: The normed fit index (NFI).
calculateNNFI
: The non-normed fit index (NNFI). Also called the Tucker-Lewis index (TLI).
calculateRMSEA
: The root mean square error of approximation (RMSEA).
calculateRMSTheta
: The root mean squared residual covariance matrix of the outer model residuals (RMS theta).
calculateSRMR
: The standardized root mean square residual (SRMR).
See the Fit indices section of the cSEM website for details on the implementation.