Hi,
I asked this question before, which was hidden in a bunch of
questions. I repharse it here and hope I can get some help this time:
I have 2 contingency tables which have the same group variable Y. I
want to compare the strength of association between X1/Y and X2/Y. I
am not sure if comparing p-values IS the way even though the
probability of seeing such "weird" observation under H0 defines
p-value and it might relate to the strength of association somehow.
But I read the following statement from Alan Agresti's "An
Introduction to Categorical Data Analysis" :
"Chi-squared tests simply indicate the degree of EVIDENCE for an
association....It is sensible to decompose chi-squared into
components, study residuals, and estimate parameters such as odds
ratios that describe the STRENGTH OF ASSOCIATION".
Can I do this "decomposition" in R for the following example including
2 contingency tables?
> tab1<-array(c(11266, 125, 2151526, 31734), dim=c(2,2))
> tab1
[,1] [,2]
[1,] 11266 2151526
[2,] 125 31734
> tab2<-array(c(43571, 52, 2119221, 31807), dim=c(2,2))
> tab2
[,1] [,2]
[1,] 43571 2119221
[2,] 52 31807
BTW, is there some good forum on the theory of statistics? r-help is a
good one but I don't want to bother people by asking some questions
weakly associated with R here.
Thanks,
--
Weiwei Shi, Ph.D
"Did you always know?"
"No, I did not. But I believed..."
---Matrix III
______________________________________________
[email protected] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
