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Extract statistics from lm()

4 messages · Christofer Bogaso, David Winsemius, Tobias Verbeke +1 more

Christofer Bogaso
# 
Hi, perhaps this question was answered previously however I could not find
them. My problem is how how to extract a particular statistic from the
result given by lm(). For e.g.

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)
Call:
lm(formula = weight ~ group)

Residuals:
    Min      1Q  Median      3Q     Max 
-1.0710 -0.4938  0.0685  0.2462  1.3690 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)   5.0320     0.2202  22.850 9.55e-15 ***
groupTrt     -0.3710     0.3114  -1.191    0.249    
---
Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 

Residual standard error: 0.6964 on 18 degrees of freedom
Multiple R-squared: 0.07308,    Adjusted R-squared: 0.02158 
F-statistic: 1.419 on 1 and 18 DF,  p-value: 0.249 


Here I want to extract the values of "t-stat", "Pr(>|t|)" individually. Can
anyone please guide me how to get them?
David Winsemius
# 
http://finzi.psych.upenn.edu/R/Rhelp08/archive/147713.html
On Feb 28, 2009, at 2:21 PM, Bogaso wrote:

            

      
      
      
    

        

      
      
    

  
  


  


      

    

    

      
      

        


  

        

      Tobias Verbeke
    

    

      
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Hi,

            

      
      
      
    

        
summaryD9 <- summary(lm.D9 <- lm(weight ~ group))
(coefD9 <- coef(summaryD9))
coefD9[, "t value"]
coefD9[, "Pr(>|t|)"]

In order to get an overview of the structure of an object
you can use the str function as in:

str(summaryD9)

HTH,
Tobias

  
  


  


      

    

    

      
      

        


  

        

      Albyn Jones
    

    

      
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Look at the data structure produced by summary()

            

      
      
      
    

        
[1] "call"          "terms"         "residuals"     "coefficients"
  [5] "aliased"       "sigma"         "df"            "r.squared"
  [9] "adj.r.squared" "fstatistic"    "cov.unscaled"

Now look at the data structure for the coefficients in the summary:

            

      
      
      
    

        
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

            

      
      
      
    

        
[1] "matrix"

            

      
      
      
    

        
(Intercept)    groupTrt
   22.850117   -1.191260

albyn

Quoting Bogaso <bogaso.christofer at gmail.com>: