Factor analysis is a statistical method that is used to
determine the number of underlying dimensions contained in a set
of observed variables and to identify the subset of variables
that corresponds to each of the underlying dimensions. The
underlying dimensions are referred to as continuous latent
variables or factors. The observed variables are referred to as
factor indicators. There are two types of factor analysis:
exploratory factor analysis (EFA) and confirmatory factor
analysis (CFA). CFA is appropriate in situations where the
dimensionality of a set of variables for a given population is
already known because of previous research. The task is not to
determine the dimensionality of a set of variables or to find
the pattern of the factor loadings. Instead, CFA may be used to
investigate whether the established dimensionality and factor-
loading pattern fits a new sample from the same population. This
is the confirmatory aspect of the analysis. CFA may also be used
to investigate whether the established