entropyFit: Entropy Fit Index

Description Usage Arguments Value Author(s) References See Also Examples

Description

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

Usage

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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 <[email protected]> and Robert Moulder <[email protected]>

References

Golino, H. F., Moulder, R., Shi, D., Christensen, A. P., Neito, M. D., Nesselroade, J. R., & Boker, S. M. (under review) Entropy Fit Index: A new fit measure for assessing the structure and dimensionality of multiple latent variables. Retrieved from: https://www.researchgate.net/profile/Hudson_Golino/publication/333753928_Entropy_Fit_Index_A_New_Fit_Measure_for_Assessing_the_Structure_and_Dimensionality_of_Multiple_Latent_Variables/

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

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

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


## End(Not run)

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

hfgolino/EGA documentation built on Aug. 16, 2019, 2:50 a.m.