values from a linear model

-----Oorspronkelijk bericht-----
Van: r-help-bounces op stat.math.ethz.ch 
[mailto:r-help-bounces op stat.math.ethz.ch] Namens Manuele Pesenti
Verzonden: dinsdag 24 juli 2007 12:03
Aan: r-help op stat.math.ethz.ch
Onderwerp: [R] values from a linear model

Dear R users,
how can I extrapolate values listed in the summary of an lm 
model but not directly available between object values such 
as the the standard errors of the calculated parameters?

for example I got a model:

mod <- lm(Crd ~ 1 + Week, data=data)

and its summary:

summary(mod)

Call:
lm(formula = Crd ~ 1 + Week, data = data, model = TRUE, y = TRUE)

Residuals:
       Min         1Q     Median         3Q        Max 
-4.299e-03 -1.653e-03  2.628e-05  1.291e-03  5.130e-03 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)    
(Intercept) 1.000e+01  3.962e-04 25238.73   <2e-16 ***
Week        5.038e-04  6.812e-06    73.96   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.001966 on 98 degrees of freedom
Multiple R-Squared: 0.9824,     Adjusted R-squared: 0.9822 
F-statistic:  5469 on 1 and 98 DF,  p-value: < 2.2e-16

I'm interested in values of Std. Error of coefficients...

thank you very much

Best regards
	Manuele

--
Manuele Pesenti
	manuele op inventati.org
	amicogodzilla op jabber.linux.it
	http://mpesenti.polito.it

Dear R users,
how can I extrapolate values listed in the summary of an lm model 
but not
directly available between object values such as the the standard 
errors of
the calculated parameters?

for example I got a model:

mod <- lm(Crd ~ 1 + Week, data=data)

and its summary:

summary(mod)

Call:
lm(formula = Crd ~ 1 + Week, data = data, model = TRUE, y = TRUE)

Residuals:
      Min         1Q     Median         3Q        Max
-4.299e-03 -1.653e-03  2.628e-05  1.291e-03  5.130e-03

Coefficients:
            Estimate Std. Error  t value Pr(>|t|)
(Intercept) 1.000e+01  3.962e-04 25238.73   <2e-16 ***
Week        5.038e-04  6.812e-06    73.96   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.001966 on 98 degrees of freedom
Multiple R-Squared: 0.9824,     Adjusted R-squared: 0.9822
F-statistic:  5469 on 1 and 98 DF,  p-value: < 2.2e-16

I'm interested in values of Std. Error of coefficients...

thank you very much

Best regards
Manuele

-- 
Manuele Pesenti
manuele at inventati.org
amicogodzilla at jabber.linux.it
http://mpesenti.polito.it

Dear R users,
how can I extrapolate values listed in the summary of an lm model but not 
directly available between object values such as the the standard errors
of 
the calculated parameters?

for example I got a model:

mod <- lm(Crd ~ 1 + Week, data=data)

and its summary:

summary(mod)

Call:
lm(formula = Crd ~ 1 + Week, data = data, model = TRUE, y = TRUE)

Residuals:
       Min         1Q     Median         3Q        Max 
-4.299e-03 -1.653e-03  2.628e-05  1.291e-03  5.130e-03 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)    
(Intercept) 1.000e+01  3.962e-04 25238.73   <2e-16 ***
Week        5.038e-04  6.812e-06    73.96   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.001966 on 98 degrees of freedom
Multiple R-Squared: 0.9824,     Adjusted R-squared: 0.9822 
F-statistic:  5469 on 1 and 98 DF,  p-value: < 2.2e-16

I'm interested in values of Std. Error of coefficients...

thank you very much

Dear R users,
how can I extrapolate values listed in the summary of an lm model but not
directly available between object values such as the the standard errors of
the calculated parameters?