Hi, I am trying to reconcile anova table in R (summary(lm)) with individual t.test.
datafilename="http://personality-project.org/R/datasets/R.appendix1.data"
data.ex1=read.table(datafilename,header=T)   #read the data into a table
summary(lm(Alertness~Dosage,data=data.ex1))

gives:

Call:
lm(formula = Alertness ~ Dosage, data = data.ex1)

Residuals:
   Min     1Q Median     3Q    Max 
-8.500 -2.437  0.250  2.687  8.500 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)   32.500      2.010  16.166 6.72e-11 ***
Dosageb       -4.250      2.659  -1.598 0.130880    
Dosagec      -13.250      3.179  -4.168 0.000824 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 4.924 on 15 degrees of freedom
Multiple R-squared: 0.5396,     Adjusted R-squared: 0.4782 
F-statistic: 8.789 on 2 and 15 DF,  p-value: 0.002977 

As far as I understand it the lines "Dosageb" and "DosageC" represent the difference between DosageA and the other two dosages.
My question is this: are these differences and the p-values associated with them the same as a t.test or pairwise.t.test on these groups? If I do t.tests, I get different values for t and p-value from those in the anova table above.
Can someone please explain what the discrepancy is?
Thanks



      
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