p-level in packages mgcv and gam
Thomas Lumley <tlumley at u.washington.edu> writes:
Bob, on the other hand, chooses the amount of smoothing depending on the data. When a 4 df smooth fits best he ends up with the same model as Alice and the same p-value. When some other df fits best he ends up with a different model and a *smaller* p-value than Alice.
This doesn't actually follow, unless the p-value (directly or indirectly) found its way into the definition of "best fit". It does show the danger, though.
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