Correct the Bad COP two-part model decomposition - #488
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Summary
Why this matters
Conditioning on a common effect opens a path and creates collider or selection bias. Conditioning on a mediator instead blocks part of the total effect and changes the estimand to a direct effect. The revised transition keeps these mechanisms separate and explains why a variable must be chosen from its causal role, not merely from how well it predicts treatment or outcome.
The previous Bad COP section also said that estimating participation and the positive outcome separately is biased. That is too broad: two-part models are valid for the marginal mean when their components are recombined. The actual problem is conditioning on the observed post-treatment event Y > 0 and interpreting m_1 - m_0 as a causal effect for one common population. The treated-positive group contains units with Y_1 > 0, while the control-positive group contains units with Y_0 > 0. Those are generally different principal-stratum mixtures even in a randomized experiment.
The rewrite preserves the warning while locating it precisely: the mistake is the causal interpretation of the selected contrast, not the two-part modeling strategy itself.
Validation
The full build retains one unrelated pre-existing Chapter 21 lexer warning.
Closes #261
Closes #385
Closes #421
Closes #455