regression coefficient for different factors

You have received suggestions about this already, but you may want to consider something like this as an alternative:

require(english)
lev <- as.character(as.english(0:9))
dat <- data.frame(f = factor(sample(lev, 500,

+                   rep=TRUE), levels = lev),
+                   B = rnorm(500))

dat <- within(dat, A <- 2 + 3*B + rnorm(B))

### method 1: using a loop
coefs <- sapply(levels(dat$f),

+                 function(x) coef(lm(A ~ B, dat,
+                                     subset = f == x)))

t(coefs)

(Intercept)        B
zero     1.967234 2.795218
one      1.864298 3.048861
two      1.978757 2.893950
three    2.035777 2.796963
four     2.092047 2.826677
five     2.263936 3.229843
six      1.740911 3.114069
seven    1.975918 3.090971
eight    2.064802 3.048225
nine     2.030697 3.059960

### Greg Snow's suggeston - use lmList
require(nlme)
coef(lmList(A ~ B | f, dat))

(Intercept)        B
zero     1.967234 2.795218
one      1.864298 3.048861
two      1.978757 2.893950
three    2.035777 2.796963
four     2.092047 2.826677
five     2.263936 3.229843
six      1.740911 3.114069
seven    1.975918 3.090971
eight    2.064802 3.048225
nine     2.030697 3.059960

Bill Venables

Dear R-helpers,

In my dataset I have two continuous variable (A and B) and one factor.
I'm investigating the regression between the two variables usign the command
lm(A ~ B, ...)
but now I want to know the regression coefficient (r2) of A vs. B for every factors.
I know that I can obtain this information with excel, but the factor have 68 levels...maybe [r] have a useful command.

Thanks,

Francesco Nutini

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