EFA does not test the latent variable model; it simply identifies dimensions of shared variance among the items factor-analyzed. That is because EFA does not impose the same specificity on a model. EFA-derived factors represent variance shared by a set of variables, but variables can and do load on more than one factor. Of course, simple structure is the typical goal for EFA analyses, but simple structure is neither absolute nor evaluated quantitatively. There is no single definition of adequate simple structure. Multiple factors can, and often do, reflect variance shared with the same variable. CFA, as typically used, imposes absolute simple structure.
