The psychometric house-of-mirrors: the effect of measurement distortions on agent-based models’ predictions

Agent-based models (ABMs) often rely on psychometric constructs such as  ‘opinions’, ‘stubbornness’, ‘happiness’, etc. The measurement process for  these constructs is quite different from the one used in physics as there is  no standardized unit of measurement for opinion or happiness.  Consequently, measurements are usually affected by ‘psychometric distortions,’ which can substantially impact models’ predictions. Even if distor?tions are well known in psychometrics, their existence and nature is  obscure to many researchers outside this field. In this paper, we introduce  distortions to the ABM community. Initially, we show where distortions  come from and how to observe them in real-world data. We then show  how they can strongly impact predictions, qualitative comparison with  data and the problem they pose for validation of models. We conclude  our analysis by discussing how researchers may mitigate this problem and highlight possible future modelling trends that will address this problem.