Model fit refers to how well a statistical model represents the data it is intended to explain. It assesses the accuracy of predictions made by the model and is essential for understanding whether the chosen model is appropriate for the underlying data. Good model fit ensures that the relationships identified in the model accurately reflect real-world patterns, which is critical in methods like regression analysis, variable selection, and evaluating model performance using criteria.
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