[R] Strange paradox
bgunter@4567 @end|ng |rom gm@||@com
Fri Oct 5 16:42:55 CEST 2018
This list is about R programming. Statistics questions, which this is, are
generally off topic here. Try posting on a statistics list like
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Fri, Oct 5, 2018 at 1:48 AM CHATTON Anne via R-help <r-help using r-project.org>
> I am currently analysed two nested models using the same sample. Both the
> simpler model (Model 1 ~ x1 + x2) and the more complex model (Model 2 ~ x1
> + x2 + x3 + x4) yield the same adjusted R-square. Yet the p-value
> associated with the deviance statistic is highly significant (p=0.0047),
> suggesting that the confounders (x3 and x4) account for the prediction of
> the dependent variable.
> Does anyone have an explanation of this strange paradox?
> Thank you for any suggestion.
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