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. 2007 Apr;21(2):118-41.
doi: 10.1521/pedi.2007.21.2.118.

A bifactor approach to modeling the structure of the psychopathy checklist-revised

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A bifactor approach to modeling the structure of the psychopathy checklist-revised

Christopher J Patrick et al. J Pers Disord. 2007 Apr.

Abstract

To date, models of the structure of psychopathy as assessed by the Psychopathy Checklist-Revised (PCL-R) have taken a higher-order approach in which the factors of the PCL-R are modeled as correlated elements of a higher-order psychopathy construct. Here, we propose an alternative structural model of the PCL-R, the bifactor model, which accounts for the covariance among PCL-R items in terms of a general factor reflecting the overlap across all items, and independent subfactors reflecting the unique coherency among particular groups of items. We present examples of how this alternative structural model can account for diverging associations between different subsets of PCL-R items and external criteria in the domains of personality and psychopathology, and we discuss implications of the bifactor model for future research on the conceptualization and assessment of psychopathy.

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Figures

FIGURE 1
FIGURE 1
Depiction of alternative higher-order and bifactor models incorporating six manifest indicators.
FIGURE 2
FIGURE 2
Scree plot for exploratory factor analysis of the 20 PCL-R indicators in the current study sample (N = 593).
FIGURE 3
FIGURE 3
Structural model of relations between general and specific factors of the PCL-R bifactor model and the latent Externalizing variable. AAB = Adult antisocial behavior (i.e., the adult criteria for antisocial personality disorder); CD = Conduct disorder (i.e., child criteria for antisocial personality disorder); ADS = Alcohol dependence scale; SDAST = Short drug abuse screening test; MPQ AG and CL = Aggression and Control primary scales of the Multidimensional Personality Questionnaire. Structural coefficients in bold and italics are significant at p < .01. All factor loadings on the latent Externalizing variable are significant at p < .01.

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