The
"factanal" object is implemented as a list
with the following components:
VALUE:
loadings
orthogonal matrix of class
"loadings" giving the loadings for each factor.
The first column is the linear combination of columns of
x defining
the first factor , etc.
uniquenesses
vector of the standardized uniquenesses for each variable.
correlation
the correlation matrix of the data.
This is what is being modeled.
criteria
information on the optimization.
In the case of a principal factor solution, this merely gives the number of
iterations used.
For maximum likelihood the objective is also given.
factors
the number of factors in the model.
dof
the number of degrees of freedom for the model.
method
character string giving the method used.
center
vector of centers for the variables.
scale
vector of numbers by which the variables are scaled (the square root of
the diagonal of the input or computed covariance matrix).
n.obs
the number of observations on which the estimates are based.
This may not be present if
covlist was used.
scores
matrix of factor scores with a
"type" attribute stating which type of
scores were computed.
This will not be present if the
scores argument to
factanal was
FALSE
or if there were no data from which to compute scores.
terms
the terms object of the formula.
This is not present if a formula was not used.
call
an image of the call to
factanal.
n.obs
the number of observations on which the estimates are based.
This may not be present if
covlist was used.