[R] Strange paradox
|r|end|y @end|ng |rom yorku@c@
Sat Oct 6 18:14:31 CEST 2018
Yes-- there's no paradox; the adjusted R^2 and deviance are looking
at/testing different things.
Also you don't say *what* deviance you are looking at, but
your interpretation of the deviance is probably wrong.
A significant test for
says that x3 & x4 add significantly to prediction, over and above x1, x2
On 10/5/2018 4:45 AM, CHATTON Anne via R-help wrote:
> 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.
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept. & Chair, ASA Statistical Graphics Section
York University Voice: 416 736-2100 x66249 Fax: 416 736-5814
4700 Keele Street Web: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
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