Should pre-intervention outcome variable Y0 be excluded from counterfactual model based on causal diagram? Based on the causal diagram below, where:

*

*Y1 is the outcome in the post-intervention period,

*Y0 is the pre-intervention outcome,

*X is a Yes/No healthcare intervention, and

*Z1 & Z2 represent various confounder variables (diagnoses, geography, etc.).

Shouldn't Y0 be excluded from the counterfactual model estimating the effect of X on Y1 given it is both a collider and mediator variable?
Is there any reason not to exclude Y0 from the study?


$Y_0$ is not a mediator; it is a confounder. You must adjust for it. If $Z_1$ and $Z_2$ were not observed, this would induce what's sometimes called "butterfly bias"; but if you can adjust for them, then all confounding is removed. The sole minimally sufficient adjustment set is $Y_0$, $Z_1$, and $Z_2$.
