MAXLIKE_FA {EFA.dimensions} R Documentation

## Maximum likelihood factor analysis

### Description

Maximum likelihood factor analysis

### Usage

MAXLIKE_FA(data, corkind, Nfactors=NULL, Ncases=NULL, rotate, ppower, verbose)

### Arguments

 data An all-numeric dataframe where the rows are cases & the columns are the variables, or a correlation matrix with ones on the diagonal.The function internally determines whether the data are a correlation matrix. corkind The kind of correlation matrix to be used if data is not a correlation matrix. The options are 'pearson', 'kendall', 'spearman', 'gamma', and 'polychoric'. Required only if the entered data is not a correlation matrix. Nfactors The number of factors to extract. Ncases The number of cases. Required only if data is a correlation matrix. rotate The factor rotation method. The options are: 'PROMAX', 'VARIMAX', and 'none'. ppower The power value to be used in a promax rotation (required only if rotate = 'PROMAX'). Suggested value: 3 verbose Should detailed results be displayed in console? TRUE (default) or FALSE

### Details

This function relies heavily on the R factanal function, and it uses the fa from the psych package when factanal produces an error.

### Value

A list with the following elements:

 totvarexplNOROT The eigenvalues and total variance explained totvarexplROT The rotation sums of squared loadings and total variance explained for the rotated loadings loadingsNOROT The unrotated factor loadings loadingsROT The rotated factor loadings (for varimax rotation) structure The structure matrix (for promax rotation) pattern The pattern matrix (for promax rotation) correls The correlations between the factors (for promax rotation) cormat_reproduced The reproduced correlation matrix, based on the rotated loadings chisqMODEL The model chi square statistic dfMODEL The model degrees of freedom pvalue The model p-value fit_coefficients Model fit coefficients

### Author(s)

Brian P. O'Connor

### References

Reyment, R., Joreskog, K., & Marcus, L. F. (1996). Applied Factor Analysis in the Natural Sciences. Cambridge, MA: Cambridge University Press.

### Examples


# the Harman (1967) correlation matrix
MAXLIKE_FA(data_Harman, Nfactors = 2, Ncases = 305,
rotate='PROMAX', ppower = 4, verbose=TRUE)

# Rosenberg Self-Esteem scale items
MAXLIKE_FA(data_RSE, corkind='gamma', Nfactors = 2,
rotate='PROMAX', ppower = 4, verbose=TRUE)

# NEO-PI-R scales
MAXLIKE_FA(data_NEOPIR, corkind='pearson', Nfactors = 5,
rotate='PROMAX', ppower = 4, verbose=TRUE)



[Package EFA.dimensions version 0.1.7.4 Index]