Latent Correlations Between Trait Aggression and Trait Antagonism
Creators: name: Chester, David
Publisher: name: Open Science Framework
Year: 2022
Subjects: subject: Personality and Social Contexts
subject: Social Psychology
subject: Social and Behavioral Sciences
subject: Psychology
subject: FOS: Psychology

description: Trait aggression remains an imperfectly understood personality construct without a major theoretical framework in which to reside. In this project, I will test the prediction that the antagonism (low agreeableness) factor of the Five Factor Model (FFM) of personality will account for the overwhelming majority of the variance in trait aggression (latent correlations &gt; .60). Other FFM factors will exhibit latent correlations &lt; |.60|. These predictions are supported by a wealth of evidence that places antagonism at the core of aggressive behavior: DeLisi, M. (2019). Antagonism and crime. In The handbook of antagonism (pp. 297-309). Academic Press. Hyatt, C. S., Zeichner, A., &amp; Miller, J. D. (2019). Laboratory aggression and personality traits: A meta-analytic review. Psychology of Violence, 9(6), 675. Vize, C. E., Collison, K. L., Miller, J. D., &amp; Lynam, D. R. (2020). The “core” of the dark triad: A test of competing hypotheses. Personality Disorders: Theory, Research, and Treatment, 11(2), 91. Vize, C. E., Miller, J. D., &amp; Lynam, D. R. (2018). FFM facets and their relations with different forms of antisocial behavior: An expanded meta-analysis. Journal of Criminal Justice, 57, 67-75. I ran an exploratory analysis on the data of 355 undergraduates who completed the Brief Aggression Questionnaire (BAQ) and the IPIP-NEO-120. This factor analysis modeled the latent correlations between trait aggression (indicated by the Physical Aggression, Verbal Aggression, Anger, and Hostility subscales) and all five FFM factors (each factor indicated by its six underlying facets), simultaneously. This model revealed that the antagonism facet of the FFM accounted for the overwhelming majority of the variance in trait aggression (latent r = .90), whereas the other four factors only accounted for a relatively small amount of variance in trait aggression (latent rs: conscientiousness = -.29, neuroticism = .22, extraversion = -.01, openness = -.03). I will now seek to confirm these analyses by replicating them in a combined dataset constructed from several existing laboratory studies on undergraduate participants who completed the 29-item Buss-Perry Aggression Questionnaire measure of trait aggression and the 44-item Big Five Inventory (7 studies, combined N = 893). I will use the lavaan package for R to run factor analyses for each FFM facet using the following design: LatentCorr.mod &lt;- 'BPAQtotal =~ BPAQphysical + BPASverbal + BPAQanger + BPAQhostility BFIagreeableness =~ BFI.2 + BFI.7 + BFI.12 + BFI.17 + BFI.22 + BFI.27 + BFI.32 + BFI.37 + BFI.42 BFIconscientious =~ BFI.3 + BFI.8 + BFI.13 + BFI.18 + BFI.23 + BFI.28 + BFI.33 + BFI.38 + BFI.43 BFIextraversion =~ BFI.1 + BFI.6 + BFI.11 + BFI.16 + BFI.21 + BFI.26 + BFI.31 + BFI.36 BFIneuroticism =~ BFI.4 + BFI.9 + BFI.14 + BFI.19 + BFI.24 + BFI.29 + BFI.34 + BFI.39 BFIopenness =~ BFI.5 + BFI.10 + BFI.15 + BFI.20 + BFI.25 + BFI.30 + BFI.35 + BFI.40 + BFI.41 + BFI.44' fitmod &lt;- cfa(LatentCorr.mod, data=[Dataset], missing='ML') summary(fitmod, fit.measures=TRUE, standardized = TRUE) I will then report the standardized latent correlations for each FFM factor. I will interpret that my hypotheses if the latent correlation between trait aggression and agreeableness is more negative than -.60, and if the latent correlations between trait aggression and the four other FFM factors are &lt; |.60|.