[R] interpret a p-value result as a significance of a linear regression in terms of sigmas
Peter Dalgaard
pd@|gd @end|ng |rom gm@||@com
Wed Jun 20 13:45:57 CEST 2018
Sorry to say so, but you seem confused.
The "sigma" in physics parlance is presumably the s.e. of the estimate so the "number of sigmas" equal the t statistic, in this case 5.738. However, use of that measure ignores the t distribution, effectively assuming that there are infinite df (and 24 in not quite infinite).
- pd
> On 20 Jun 2018, at 12:53 , jean-philippe <jeanphilippe.fontaine using gssi.infn.it> wrote:
>
> dear R community,
>
> I am running a linear regression for my dataset between 2 variables (disk mass and velocities).
> This is the result returned by the summary function onto the lm object for one of my dataset.
>
> Call:
> lm(formula = df$md1 ~ df$logV, data = df)
>
> Residuals:
> Min 1Q Median 3Q Max
> -0.64856 -0.16492 0.04127 0.18027 0.45727
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 6.2582 0.2682 23.333 < 2e-16 ***
> df$logV 1.2926 0.2253 5.738 6.5e-06 ***
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> Residual standard error: 0.3067 on 24 degrees of freedom
> Multiple R-squared: 0.5784, Adjusted R-squared: 0.5609
> F-statistic: 32.93 on 1 and 24 DF, p-value: 6.504e-06
>
>
> I am interested to give the significance in terms of sigmas (as generally done in particle physics, see for instance the 7 \sigma discovery of the Higgs particle)
> of my regression.
> For this, if I understood well, I should look at the p-value for the F-statistic which is in this univariate linear regression the same as the one for logV.
>
> My question is, am I right if I state that the significance in terms of sigmas (sign) is given by: p = 2*(1-pnorm(sign)) since I guess the p-value returned by R is for a two sided test (and assuming Gaussianity for my dataset)?
>
> Otherwise is there any way to get the significance of this linear regression in terms of sigmas?
>
> I would have a similar question also, as extension, for a multivariate linear regression for which the p-value associated to F statistics is not the same as the p-value for each variable of the regression.
>
>
>
> Thanks in advance,
>
>
> Best Regards
>
>
> Jean-Philippe Fontaine
>
> --
> Jean-Philippe Fontaine
> PhD Student in Astroparticle Physics,
> Gran Sasso Science Institute (GSSI),
> Viale Francesco Crispi 7,
> 67100 L'Aquila, Italy
> Mobile: +393487128593, +33615653774
>
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--
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
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