Factor analytic approaches to personality item-level data

Factor analysis models have played a central role in formulating conceptual models in personality and personality assessment, as well as in empirical examinations of personality measurement instruments. Yet, the use of item-level data presents sped al problems for factor analysis applications. In this article, we review recent developments in factor analysis that are appropriate for the type of item-level data often collected in personality. Included in this review are discussions of how these developments have been addressed in the context of two different (but formally related) statistical models: item response theory (IRT; Hambleton, Swaminathan, & Rogers, 1991) and structural equation modeling (Bollen, 1989) for item-level data. We also discuss the relevance of item scaling in the context of these models. Using the restandardization data for the Minnesota Multiphasic Personality Inventory-2 Scale (cf. Butcher, Dahlstrom, Graham, Tellegen, & Kaemmer, 1989), we show brief examples of the utility of these approaches to address basic questions about responses to personality scale items regarding: (a) scale dimensionality and general item properties, (b) the ''appropriateness'' of the observed responses, and (c) differential item functioning across subsamples. Implications for analyses of personality item-level data in the IRT and factor analytic traditions are discussed.