Cases can be excluded from study because their nonoccurrence is overdetermined

Evidence

The Rule of Exclusion depends on the analyst having good knowledge about one or more “eliminatory variables” that are important enough to remove a case from the domain of relevant observations all by themselves. These eliminatory variables may be necessary causes of the positive outcome of interest, or they may be sufficient causes of the negative outcome. It is not uncommon for multiple eliminatory variables to be present in a given case, and thus for the zero value on the dependent variable to be overdetermined. For example, one can come up with many reasons why social revolution in the United States in 1900 was theoretically impossible. Given that non–social revolution was overdetermined, it makes little sense to use the United States when testing theories of social revolution. — Gary Goertz, Social Science Concepts, 1164

Categorization

• XREF: Overdetermination of a negative outcome maps onto Mill’s methods and the ‘doomed case’ problem in causal inference.
• SEED: Angle: why the US keeps appearing as a null case in comparative revolution studies — a piece on picking irrelevant negatives.