tefi {EGAnet}

R Documentation

Total Entropy Fit Index using Von Neumman's entropy (Quantum Information Theory) for correlation matrices

Description

Computes the fit (TEFI) of a dimensionality structure using Von Neumman's entropy when the input is a correlation matrix. Lower values suggest better fit of a structure to the data.

Usage

tefi(data, structure)

Arguments

data	A dataframe or correlation matrix
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:

VN.Entropy.Fit	The Entropy Fit Index using Von Neumman's entropy
Total.Correlation	The total correlation of the dataset
Average.Entropy	The average entropy of the dataset

Author(s)

Hudson 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]

## Not run: 
# Estimate EGA model
ega.wmt <- EGA(data = wmt, model = "glasso")


## End(Not run)

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

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