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If you had two models - one with a better fit, and one with predictors of higher significance - which one would you choose?

Keep in mind that both models are considered a good fit. One has a 3% better predictive capabilities. And also all the same predictors are significant in both models, but in one model (with a slightly worse fit) they are slightly more significant.

IvLi
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    What do you want to do with the model? Do you want to use it to explain some variable? Or do you want to produce forecasts of the variable? – soakley Jun 19 '13 at 00:18
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    It depends on what the model is for. If the point is to predict, you'd care more about predictive accuracy. If the point is something else, you may not care about slightly better predictive performance. – Glen_b Jun 19 '13 at 00:23
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    Please note that a good fit to the training data and predictive ability are not at all the same thing. Your question seems to suggest it. – Glen_b Jun 19 '13 at 00:51
  • Thx for the that info! My main aim is to predict, so by your comment I guess I am going to choose the model with variables of greater significance. Right? I will use the model to test a few hypothesis. – IvLi Jun 19 '13 at 14:24
  • Have a look at this question for a better understanding of data properties that impact the two measures: https://stats.stackexchange.com/questions/369554/significance-vs-goodness-of-fit-in-regression – DotPi May 11 '20 at 12:54

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