cfa
and sem
functions in the sem package.
Continue in this manner until all factors are specified.
Note that if there are not at least two unique variables selected for each factor, the
model will probably be underidentified, causing sem
to fail.
The radio buttons at the top of the dialog may be used to analyze either the correlation matrix or covariance matrix of the observed variables; to specify either correlated or orthogonal factors; and to identify the model either by setting the factor variance to 1 or by setting the first loading for each factor to 1 (establishing a ``reference indicator'' for the factor). A check box is provided to compute robust standard errors and tests.
sem
, cfa