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19age2
2008 Aug 20
1
Understanding output of summary(glm(...))
...9.560879 9.617891 9.617891 10.158160 10.592377 10.068443
>summary(glm(tmp1 ~ -1 + age, data=data.frame(as.vector(as.matrix(tmp1)), age)))$coefficients Estimate Std. Error t value Pr(>|t|)age1 9.541423 0.1611603 59.20456 3.380085e-19age2 10.083694 0.1611603 62.56935 1.479781e-19age3 9.739813 0.1611603 60.43557 2.485380e-19age4 9.748297 0.1611603 60.48821 2.453251e-19age5 10.109218 0.1611603 62.72773 1.424913e-19
m1 <- data.frame(tmp1, gp)
>sapply(age, function(x) sd(m1[m1[,"age"]==x,1])) [1] 0.1580745 0.1580745 0.1580745 0.1580745 0.1013207 0.1013207 0.1...