The Big Five Personality Traits Are Composites Rather Than Common Causes

The Big Five personality traits are among the most frequently measured psychological traits. They are often treated as common causes of the Big Five items in reflective measurement models such as factor analysis models and item response theory models. For example, extraversion items are modeled as reflective indicators influenced by the latent variable extraversion. However, the reflective measurement model’s assumption of unidimensionality is implausible because the Big Five do not correspond to five biological, environmental, or mental entities that could serve as common causes. The reflective model’s assumption of local independence is also implausible due to direct causal effects, semantic overlap, and logical consistencies among the Big Five items. Despite the implausibility of a reflective model, researchers continue to use methods and theories that implicitly or explicitly assume a reflective measurement model. As an alternative, I propose a composite-formative measurement model. A shift from a reflective to a composite-formative model implies that researchers should use composite-formative rather than reflective measurement models in structural equation models. Additionally, item retest reliabilities rather than Cronbach’s alpha or McDonald’s omega should be used to estimate reliability. The composite-formative model for the Big Five is as useful as the reflective measurement model for description and prediction. However, other predictive approaches are more accurate, and the Big Five composites are hardly useful for investigating causal effects. Overall, the composite-formative model overcomes the implausibility of the assumptions of the reflective measurement model while enabling personality researchers to continue to use the Big Five for descriptive research purposes.