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 â***â 0.001 â**â 0.01 â*â 0.05 â.â 0.1 â â 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 [[alternative HTML version deleted]]
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