Maximum likelihood factor analysis
Maximum likelihood factor analysis
MAXLIKE_FA(data, corkind, Nfactors=NULL, Ncases=NULL, rotate, ppower, verbose)
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 |
This function relies heavily on the R factanal function, and it uses the fa from the psych package when factanal produces an error.
A list with the following elements:
eigenvalues |
The eigenvalues |
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 |
Brian P. O'Connor
Reyment, R., Joreskog, K., & Marcus, L. F. (1996). Applied Factor Analysis in the Natural Sciences. Cambridge, MA: Cambridge University Press.
# 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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.