From: David Winsemius <dwinsemius_at_comcast.net>

Date: Thu, 27 Nov 2008 10:00:36 -0500

Date: Thu, 27 Nov 2008 10:00:36 -0500

On Nov 27, 2008, at 9:49 AM, David Winsemius wrote:

> Have you looked at results of str on a regression object? I would

*> not think that there would be a single p.value associated with such
**> a beast, but that there might be if you examined individual
**> coefficients.
**>
**> ? coefficients
**> ?coef
**>
*

That wasn't on as on point as I thought. Take a look at this screen
dialog:

> x <- 1:5; coef(lm(c(1:3,7,6) ~ x))

(Intercept) x -0.7 1.5

> str(coef(lm(c(1:3,7,6) ~ x)))

Named num [1:2] -0.7 1.5

- attr(*, "names")= chr [1:2] "(Intercept)" "x" > anova(lm(c(1:3,7,6) ~ x)) Analysis of Variance Table

Response: c(1:3, 7, 6)

Df Sum Sq Mean Sq F value Pr(>F) x 1 22.5000 22.5000 15.698 0.02872 *Residuals 3 4.3000 1.4333

--- Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1 > str(anova(lm(c(1:3,7,6) ~ x))) Classes anova and 'data.frame': 2 obs. of 5 variables: $ Df : int 1 3 $ Sum Sq : num 22.5 4.3 $ Mean Sq: num 22.5 1.43 $ F value: num 15.7 NA $ Pr(>F) : num 0.0287 NA - attr(*, "heading")= chr "Analysis of Variance Table\n" "Response: c(1:3, 7, 6)" > anova(lm(c(1:3,7,6) ~ x))$"Pr(>F)" [1] 0.02871561 NA > anova(lm(c(1:3,7,6) ~ x))$"Pr(>F)"[1] [1] 0.02871561Received on Thu 27 Nov 2008 - 15:07:40 GMT

> --> David Winsemius>

> On Nov 27, 2008, at 4:03 AM, ales grill wrote:

>>> Dear all,>> I have wrote a code for a linear regression. I want to>> write a loop for so, that I can get estimate for pavlues for six>> predictors.>> But I am getting for estmate for only last one. How can I get>> pvalues for>> all my predictors in a loop??>>>> Anticipating your help>> Thanks>> Ales>>>>>>>>>>> mat<-matrix(rnorm(36),nrow=6)>>> mat>> [,1] [,2] [,3] [,4]>> [,5] [,6]>> [1,] 1.10536338 -0.7613770 -1.7100569 -1.8762241 -0.36579280>> 0.6465219>> [2,] -1.34836804 -0.2174270 -0.1153477 -0.1727683 -1.88406206>> 1.7484955>> [3,] 0.96814418 -2.1483727 0.5839668 -1.2361659 0.04592844>> 1.9937995>> [4,] 0.01960219 -1.2339691 0.8290761 0.1002795 -0.15952881>> 0.3969251>> [5,] 1.62343073 1.3741222 -1.2045854 0.4180127 -0.09898615>> 1.3575119>> [6,] -0.95260509 -0.1522824 -1.4257526 1.0057412 -1.20068336>> -0.4306761>>> res<-rnorm(6)>>> res>> [1] 0.2045252 -0.9824761 0.7727004 0.6439993 1.8005737 1.0167214>>>>>> pval<-NULL>>>>>> for(i in c(1:6))>> + {>> + reg<-lm(res~mat[,i])>> + reg>> + pval[i]<-reg$p.value>> + }>>> pval>> NULL>>> reg>>>> Call:>> lm(formula = res ~ mat[, i])>> Coefficients:>> (Intercept) mat[, i]>> 0.8195 -0.2557>>>> [[alternative HTML version deleted]]>>>> ______________________________________________>> R-help_at_r-project.org mailing list>> https://stat.ethz.ch/mailman/listinfo/r-help>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html>> and provide commented, minimal, self-contained, reproducible code.>> ______________________________________________> R-help_at_r-project.org mailing list> https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.

______________________________________________ R-help_at_r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.

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