Abstract
Scientific progress in all empirical sciences relies on selecting models and performing inferences from selected models. Standard statistical properties (e.g., repeated sampling coverage probability of confidence intervals) cannot be guaranteed after a model selection. This viewpoint reviews this dilemma, puts the role that pre-specification can play into perspective and illustrates model averaging as a way to relax the problem of model selection uncertainty.
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