Clarifying Personality Measurement in I-O: The Utility of Item Response Tree Models

Self-report personality measures typically seek to capture overall tendencies of individuals' behavior but do not capture potentially useful information provided by within-person variability and differences in trait relevance. We propose an item-response theory approach to simultaneously capture estimates of trait levels, within-person variability, and differences in trait relevance. In contrast to previous research, we focus on intentional within-person shifts in personality that we label adaptability. This approach was tested on a large sample (N = 983) using Amazon's Mechanical Turk. Results suggested that these three aspects can be statistically distinguished from each other and provide incremental variance in related outcomes. The ability to simultaneously capture personality trait levels, adaptability, and traitedness with self-report measures would allow researchers to better understand the role of personality in the workplace.