entropyFit {EGAnet}

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

Numeric or character vector (length = ncol(data)). 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 <[e-mail]> and Robert Moulder <[e-mail]>

References

Initial formalization and simulation
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.

Examples

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

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

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