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.

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


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)



[Package EGAnet version 1.1.0 Index]