Statistical Fatalism
Read OriginalThe article critiques the foundational assumption in statistical causal inference that a treatment's effect is fixed and doesn't change future outcomes. It argues this 'fatalism' is flawed, using the example of cancer screening trials where the publication of results itself changes the meaning and effect of the treatment offer, rendering the original experiment's conclusions invalid for future decisions.
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