How psychometric distortions affect agent-based models – New paper

I am thrilled to announce the publication of my recent article in the International Journal of Social Research Methodology titled “The psychometric house-of-mirrors: the effect of measurement distortions on agent-based models’ predictions.” In this article, we address an important issue in agent-based models (ABMs) that has been largely overlooked by many researchers: psychometric distortions.

ABMs often rely on psychometric constructs such as opinions, stubbornness, happiness, and more. However, the measurement process for these constructs differs significantly from the standardized units of measurement used in physics, for example. As a result, measurements are often affected by psychometric distortions, which can substantially impact the predictions made by these models.

In our article, we introduce the concept of distortions to the ABM community. We begin by explaining where these distortions come from and how to observe them in real-world data. We then demonstrate how they can have a significant impact on predictions, the qualitative comparison with data, and the validation of models.

We conclude our analysis by discussing how researchers can mitigate this problem and highlight possible future modeling trends that will address this issue. Our findings emphasize the importance of understanding the impact of measurement distortions on ABMs and the need for more rigorous validation methods.

I am proud to have contributed to the ABM community by shedding light on this important issue. I hope that our article will encourage researchers to consider the effects of measurement distortions when constructing and validating their models, leading to more accurate predictions and a deeper understanding of complex social phenomena.

Full article: https://www.tandfonline.com/doi/full/10.1080/13645579.2022.2137938