# [R] Regression Problem for loop

David Winsemius dwinsemius at comcast.net
Thu Nov 27 16:00:36 CET 2008

```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)"
 0.02871561         NA
> anova(lm(c(1:3,7,6) ~ x))\$"Pr(>F)"
 0.02871561

> --
> 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??
>>
>> 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
>>   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]]
>>
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