Factor Analytic Approaches to Personality Item-Level Data

Abstract

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 special 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.

The Assessment of Factorial Invariance in Need for Cognition Using Hispanic and Anglo Samples

“…Item scores from ordered categories may not meet the strict assumptions of linearity in a linear confirmatory factor analysis model (McDonald, 1999;Panter, Swygert, Dahlstrom, & Tanaka, 1997). In addition, the use of a single item to assess ethnicity perhaps resulted in questionable construct validity (Tanaka, Ebreo, Linn, & Morera, 1998 Overall, the results of this investigation suggested that the NCS-SF was configurally invariant across the two ethnic samples that we examined.…”

Body size dissatisfaction and avoidance behavior: How gender, age, ethnicity, and relative clothing size predict what some won’t try

“…The conclusions from the EFA were then confirmed using a confirmatory factor analysis (CFA) conducted on the remaining cases in a holdout sample (n = 1503). Tetrachoric correlations (see Muthén, 1984;Panter, Swygert, Dahlstrom, & Tanaka, 1997) were computed and used in all factor analyses because the ten avoidance items were dichotomously scored. Given the dichotomous, nonnormal nature of the data, these factor analyses employed a weighted least-squares estimator with mean and variance adjustment (WLSMV; Muthén, DuToit, & Spisic, 1997), which has been shown to yield accurate test model statistics under both normal and nonnormal latent response distributions (Flora & Curran, 2004) and provide superior model fit and precise factors loadings when used with dichotomously score items (Beauducel & Herzberg, 2006).…”

Analyzing Psychopathology Items: A Case for Nonparametric Item Response Theory Modeling.

“…That is, they compared the fit of the two-parameter and three-parameter logistic models (PLMs) on 15 unidimensional factor scales from the Minnesota Multiphasic Personality Inventory-Adolescent (MMPI-A; Butcher et al, 1992). Most studies apply parametric IRT models (in particular, the 2PLM and 3PLM) to investigate the quality of personality and psychopathology tests (e.g., Panter, Swygert, Dahlstrom, & Tanake, 1997;Robie, Zickar, & Schmitt, 2001;Steinberg, 1994;Waller, Thompson, & Wenk, 2000).The aim of the present study was to illustrate the usefulness of nonparametric IRT (NIRT) to construct and to analyze psychopathology and personality scales and tests. In our opinion, the use of NIRT has been underexposed in the recent personality literature (for an exception, see Santor & Ramsay, 1998).…”