How to define Unit-specific quantity of the effect of a continuous variable on another continuous one? Recently Lundberg, 2021 [1] emphasized the necessity to define a unit-specific quantity, target population, and causal diagram, to clarify the theoretical and empirical estimands of any quantitative study. The state "Every quantitative study must be able to answer the
question: what is your estimand? The estimand is the target quantity—the purpose of the
statistical analysis." However, almost all the examples I see compare the aggregate (usually average) unit-specific quantity across two groups of a dichotomous variable, such as males vs. females, treated vs. control, ...
I found no single example of analyzing the correlation between two continuous variables or the causal effect of one continuous variable on another one.
Please give me such an example or explain how one can formulate the unit-specific quantity for the causal effect of one continuous variable on another one.
References:
[1] Lundberg, I., Johnson, R., & Stewart, B. M. (2021). What is your estimand? Defining the target quantity connects statistical evidence to theory. American Sociological Review, 86(3), 532-565.

Unless you are in the rare situation where X vs Y is linear, the most sensible estimand is the continuous function relating X to a property of Y such as the median or mean.  If the relationship were linear then the (constant) slope would be sufficient.  The estimator of the regression function would be for example a regression spline.
