EFA.MRFA (version 1.1.2)

EFA.MRFA-package: Dimensionality Assesment using Minimum Rank Factor Analysis (MRFA)

Description

Package for performing Parallel Analysis using Minimum Rank Factor Analysis (MRFA) . It also include a function to perform the MRFA only and another function to compute the Greater Lower Bound step for estimating the variables communalities.

Value

parallelMRFA

Performs Parallel Analysis using Minimum Rank Factor Analysis (MRFA).

hullEFA

Performs Hull analysis for assessing the number of factors to retain.

mrfa

Performs Minimum Rank Factor Analysis (MRFA) procedure.

GreaterLowerBound

Estimates the communalities of the variables from a factor model.

Details

For more information about the methods used in each function, please go to each main page.

References

Devlin, S. J., Gnanadesikan, R., & Kettenring, J. R. (1981). Robust estimation of dispersion matrices and principal components. Journal of the American Statistical Association, 76, 354-362. 10.1080/01621459.1981.10477654

Lorenzo-Seva, U., Timmerman, M. E., & Kiers, H. A. (2011). The Hull Method for Selecting the Number of Common Factors. Multivariate Behavioral Research, 46(2), 340-364. 10.1080/00273171.2011.564527

ten Berge, J. M. F., & Kiers, H. A. L. (1991). A numerical approach to the approximate and the exact minimum rank of a covariance matrix. Psychometrika, 56(2), 309-315. 10.1007/BF02294464

Ten Berge, J.M.F., Snijders, T.A.B. & Zegers, F.E. (1981). Computational aspects of the greatest lower bound to reliability and constrained minimum trace factor analysis. Psychometrika, 46, 201-213.

Timmerman, M. E., & Lorenzo-Seva, U. (2011). Dimensionality assessment of ordered polytomous items with parallel analysis. Psychological Methods, 16(2), 209-220. 10.1037/a0023353

Examples

# NOT RUN {
## Example 1:

## perform a Parallel Analysis using an example Database with only 5 random data sets and
## using the 90th percentile of distribution of the random data
parallelMRFA(IDAQ, Ndatsets=5, percent=90)

## For speeding purposes, the number of datasets have been largely reduced. For a proper
## use of parallelMRFA, we recommend to use the default Ndatsets value (Ndatsets=500)

#Example 2:

## Perform the Hull method defining the maximum number of dimensions to be tested by the
## Parallel Analysis + 1 rule, with Maximum Likelihood factor extraction method and CAF
## as Hull index.
hullEFA(IDAQ, extr = "ML")
# }