Causal Diagrams for Structural Engineers

TL;DR

This paper introduces causal diagrams, specifically directed acyclic graphs (DAGs), to civil engineering, demonstrating how they can clarify complex causal relationships and improve research and practice in the field.

Contribution

It presents the core concepts of causal diagrams and shows their application to civil engineering problems, a novel approach for the discipline.

Findings

Civil engineers can effectively use causal diagrams to understand complex causation.

Causal diagrams help identify confounders, colliders, and mediators in engineering studies.

Application of DAGs accelerates research and practical decision-making.

Abstract

Causal diagrams are logic and graphical tools that depict assumptions about presumed causal relations. Such diagrams have proven effective in tackling a variety of problems in social sciences and epidemiology research yet remain foreign to civil engineers. Unlike the traditional means of examining relationships via multivariable regression, causal diagrams can identify the presence of confounders, colliders, and mediators. Thus, this paper hopes to introduce the big ideas behind causal diagrams (specifically, directed acyclic graphs (DAGs)) and how to create and apply such diagrams to several civil engineering problems. Findings from the presented case studies indicate that civil engineers can successfully use causal diagrams to improve their understanding of complex causation relations, thereby accelerating research and practical efforts.