# Neither measurement error nor speed–accuracy trade-offs explain the difficulty of establishing attentional control as a psychometric construct: Evidence from a latent-variable analysis using diffusion modeling

## TL;DR

This study finds that attentional control cannot be reliably measured as a single psychological trait, even when accounting for common measurement issues.

## Contribution

The paper introduces a novel method combining diffusion modeling and structural equation modeling to rigorously test attentional control as a psychometric construct.

## Key findings

- Measures of attentional control did not correlate with each other.
- Attentional control measures failed to load onto a latent variable.
- The difficulty of establishing attentional control as a psychometric construct remains unresolved.

## Abstract

Attentional control refers to the ability to maintain and implement a goal and goal-relevant information when facing distraction. Previous research has failed to substantiate strong evidence for a psychometric construct of attentional control. This could result from two methodological shortcomings: (a) the neglect of individual differences in speed–accuracy trade-offs when only speed or accuracy is used as dependent variable, and (b) the difficulty of isolating attentional control from measurement error. To overcome both issues, we combined hierarchical Bayesian Wiener diffusion modeling with structural equation modeling. We reanalyzed six datasets that included data from three to eight attentional-control tasks, and data from young and older adults. Overall, the results showed that measures of attentional control failed to correlate with each other and failed to load on a latent variable. Therefore, limiting the impact of differences in speed–accuracy trade-offs and of measurement error does not solve the difficulty of establishing attentional control as a psychometric construct. These findings strengthen the case against a psychometric construct of attentional control.