fit_measures {cSEM} | R Documentation |
Calculate fit measures.
calculateChiSquare(.object, .saturated = FALSE)
calculateChiSquareDf(.object)
calculateCFI(.object)
calculateGFI(.object, .type_gfi = c("ML", "GLS", "ULS"), ...)
calculateCN(.object, .alpha = 0.05, ...)
calculateIFI(.object)
calculateNFI(.object)
calculateNNFI(.object)
calculateRMSEA(.object)
calculateRMSTheta(.object)
calculateSRMR(
.object = NULL,
.matrix1 = NULL,
.matrix2 = NULL,
.saturated = FALSE,
...
)
.object |
An R object of class cSEMResults resulting from a call to |
.saturated |
Logical. Should a saturated structural model be used?
Defaults to |
.type_gfi |
Character string. Which fitting function should the GFI be based on? One of "ML" for the maximum likelihood fitting function, "GLS" for the generalized least squares fitting function or "ULS" for the unweighted least squares fitting function (same as the squared Euclidean distance). Defaults to "ML". |
... |
Ignored. |
.alpha |
An integer or a numeric vector of significance levels.
Defaults to |
.matrix1 |
A |
.matrix2 |
A |
See the Fit indices section of the cSEM website for details on the implementation.
A single numeric value.
calculateChiSquare()
: The chi square statistic.
calculateChiSquareDf()
: The Chi square statistic divided by its degrees of freedom.
calculateCFI()
: The comparative fit index (CFI).
calculateGFI()
: The goodness of fit index (GFI).
calculateCN()
: The Hoelter index alias Hoelter's (critical) N (CN).
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).