With models, it is easy to lose track of three essential points: (i) results depend on assumptions, (ii) changing the assumptions in apparently innocuous ways can lead to drastic changes in conclusions, and (iii) familiarity with a model’s name is no guarantee of the model’s truth. Under the circumstances, it may be the assumptions behind the model that provide the leverage, not the data fed into the model. This is a danger with experiments, and even more so with observational studies. David Freedman
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Lars Pålsson Syll considers the following as important: Statistics & Econometrics
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With models, it is easy to lose track of three essential points: (i) results depend on assumptions, (ii) changing the assumptions in apparently innocuous ways can lead to drastic changes in conclusions, and (iii) familiarity with a model’s name is no guarantee of the model’s truth. Under the circumstances, it may be the assumptions behind the model that provide the leverage, not the data fed into the model. This is a danger with experiments, and even more so with observational studies.