entropyFit {EGAnet}

R Documentation

Entropy Fit Index

Description

Computes the fit of a dimensionality structure using empirical entropy. Lower values suggest better fit of a structure to the data.

Usage

entropyFit(data, structure)

Arguments

data	Matrix or data frame. Contains variables to be used in the analysis
structure	A vector representing the structure (numbers or labels for each item). Can be theoretical factors or the structure detected by EGA

Value

Returns a list containing:

Total.Correlation	The total correlation of the dataset
Total.Correlation.MM	Miller-Madow correction for the total correlation of the dataset
Entropy.Fit	The Entropy Fit Index
Entropy.Fit.MM	Miller-Madow correction for the Entropy Fit Index
Average.Entropy	The average entropy of the dataset

Author(s)

Hudson F. Golino <hfg9s at virginia.edu>, Alexander P. Christensen <alexpaulchristensen@gmail.com> and Robert Moulder <rgm4fd@virginia.edu>

References

Golino, H., Moulder, R. G., Shi, D., Christensen, A. P., Garrido, L. E., Nieto, M. D., Nesselroade, J., Sadana, R., Thiyagarajan, J. A., & Boker, S. M. (2020). Entropy fit indices: New fit measures for assessing the structure and dimensionality of multiple latent variables. Multivariate Behavioral Research.

See Also

EGA to estimate the number of dimensions of an instrument using EGA and CFA to verify the fit of the structure suggested by EGA using confirmatory factor analysis.

Examples

# Load data
wmt <- wmt2[,7:24]


# Estimate EGA model
ega.wmt <- EGA(data = wmt, model = "glasso", plot.EGA = FALSE)



# Compute entropy indices
entropyFit(data = wmt, structure = ega.wmt$wc)

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