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Why your DAG should probably incorporate sampling and measurement processes
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DOI：10.1016/j.cois.2026.101578.png)
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Abstract
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Insect scientists are starting to use Directed Acyclic Graphs (DAGs) to display assumptions about causal relationships between variables that exist before any data have been collected. The perception appears to be that these assumptions are sufficient to determine whether observed associations between variables can be interpreted causally. But an observed association implies an observation process (sampling and measurement), and assumptions about that process are also required. We draw on the literature from other disciplines to explain how insect scientists can incorporate assumptions about sampling and measurement in DAGs. Making these assumptions explicit allows the investigator to reason more holistically about whether observed associations can be interpreted as causal effects. It also reveals that DAGs are not just a tool for causal inference; assumptions about sampling and measurement are also needed to answer descriptive and predictive questions. Hence, DAGs that incorporate these processes provide a general framework for displaying assumptions regardless of inferential goal.
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