[R] chisq.test, basic question

[Peter Dalgaard BSA]

"juli g. pausas" <juli at ceam.es> writes:

> 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?

Don't use chisq.test on proportions, only on counts. The first
analysis is correct, the second is wrong. 

-- 
   O__  ---- Peter Dalgaard             Blegdamsvej 3  
  c/ /'_ --- Dept. of Biostatistics     2200 Cph. N   
 (*) \(*) -- University of Copenhagen   Denmark      Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)             FAX: (+45) 35327907
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