This paper offers some commentary and recommendations relevant the multi-factor modeling in individual differences research. Several similarities and distinctions between oblique factor modeling, higherorder modeling, Schmid-Leiman transformations, and nested factors modeling are discussed. An empirical illustration of the various multi-factor models is presented, based on 18 items derived from three Neuroticism facets within the NEO Pl-R. Researchers are encouraged to always perform a Schmid-Leiman transformation to a higher-order model solution, as well as to consider the possibility that a nested factors model will yield superior model fit, in comparison to a higher-order model, as well as less ambiguous factor solutions. (c) 2006 Elsevier Ltd. All rights reserved.