ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2,10,20, labels=c("Ctl","Trt"))
weight <- c(ctl, trt)
lm.D9 <- lm(weight ~ group)
summary(lm.D9)$coef
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.032 0.2202177 22.850117 9.547128e-15
groupTrt -0.371 0.3114349 -1.191260 2.490232e-01
class(summary(lm.D9)$coef)
[1] "matrix"
> colnames(summary(lm.D9)$coef)
[1] "Estimate" "Std. Error" "t value" "Pr(>|t|)"
So you can get t and p-value by
>summary(lm.D9)$coef[,"t value"]
summary(lm.D9)$coef[,"Pr(>|t|)"]
If you want to get the result as matrix,just use the drop=F argument.
summary(lm.D9)$coef[,"Pr(>|t|)",drop=F]
Pr(>|t|)
(Intercept) 9.547128e-15
groupTrt 2.490232e-01
2006/6/21, Jun Ding <[EMAIL PROTECTED]>:
Hi Everyone,
I just don't know how to extract the information I
want from the summary of a linear regression model
fitting.
For example, I fit the following simple linear
regression model:
results = lm(y_var ~ x_var)
summary(results) gives me:
Call:
lm(formula = y_var ~ x_var)
Residuals:
Min 1Q Median 3Q Max
-5.9859 -1.5849 0.4574 2.0163 4.6015
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.7782 0.5948 -2.990 0.004879 **
x_var 2.1237 0.5073 4.187 0.000162 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.'
0.1 ' ' 1
I can get the esitmates (i.e. -1.7782 and 2.1237) of
coefficients by calling
results$coefficients
I think using coef(result) is a better habit.
But I don't know how to get the corresponding t values
and P values for those coefficients. I am running a
lot of regression models and I can not run 'summary'
every time to get the t and P values for each model.
Can anybody give me some hints? Thank you very much!
Best,
Jun
----------------------------
Jun Ding, Ph.D. student
Department of Biostatistics
University of Michigan
Ann Arbor, MI, 48105
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--
黄荣贵
Department of Sociology
Fudan University
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