[R] Statistically significant in linear and non-linear model

[Greg Snow]

Well here is one example where x is not significant in a linear regression:

> x <- seq( -1,1, 0.1 )
> y <- x^2 + rnorm(21,0,.1)
> summary(lm(y~x))

Would you really want to dismiss any relationship (non-linear) between x and y based on the above p-value?

--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111


> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Hsiao-nan Cheung
> Sent: Tuesday, October 07, 2008 11:47 AM
> To: R-help
> Subject: [R] Statistically significant in linear and non-linear model
>
> Hi,
>
>
>
> I have a question to ask. if in a linear regression model, the
> independent
> variables are not statistically significant, is it necessary to test
> these
> variables in a non-linear model? Since most of non-linear form of a
> variable
> can be represented to a linear combination using Taylor's theorem, so I
> wonder whether the non-linear form is also not statistically
> significant in
> such a situation.
>
>
>
> Best Regards
>
> Hsiao-nan Cheung
>
> 2008/10/08
>
>
>
>
>
>
>
>
>         [[alternative HTML version deleted]]
>
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