[R] chisq.test, basic question

[juli g. pausas]

Dear R-users,
I have a question, which I’m not sure if it is related to my
misunderstanding of basic statistics, or my misunderstanding of R, or
both.
I’ve got the counts of a 2 x 2 contingency table, and I'd like to test
the association:

m <-  matrix(c(15,28,32,135), 2, 2)
colnames(m) <- c("R-", "R+"); rownames(m) <- c("P-", "P+")
m
#    R-  R+
# P- 15  32
# P+ 28 135

chisq.test(m)  # X-squared = 4.0027, df = 1, p-value = 0.04543

Is this the correct way to test association between P and R? (I haven’t
got the original data).
My problem is that if I use percentage, then I get different results:

m2 <- 100*m/sum(m) #
chisq.test(round(m2)) # X-squared = 1.5318, df = 1, p-value = 0.2158

Should this give about the same (a part from the rounding)? Should the
degree of association between P and R be he same?  Or, am I using
chisq.test() wrongly?

Thanks in advance,

Juli


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