The concept of a broken-leg principle refers to statistical models that clarify when the model is valid and when it is not.
An example, could be the likely prediction that a person will attend an event unless they have a broken leg or some other accident, which nullifies the prediction.
Researchers do well to clarify the conditions under which their models are valid and when their models should not be applied.
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