Dear all,
I have several questions regarding fisher.test() in
R, and I'd highly appreciate any help with it.
I have a group of observations, each having people's
income, and an indicator of whether selected in or out
a program. I want to test the difference between
income of people who are in and out.
Because the distribution is far from normal, I decide
to use the fisher's exact test, using either mean or
rank as statistics.
Question 0 is: Can I do this test using fisher.test()
in R?
If so,
My first question is: Does fisher.test() offer an
option to choose the statistics? Actually it is not
clear from the help to me what statistics it uses.
Does it just compare the mean of people in and out of
the program?
My second question is: when the group is large, I
always receive a warning message such as "Fisher exact
result might not be right" when I set "hybrid=T".
When I set "hybrid=F", it does return a result of
p-value without warning message. I wonder if this
p-value is reliable or not. And, how does it get the
approximation of p-value when "hybrid=F"? Ideally, it
should randomly draw, say 1000 times, from the full
sets of permutation of assignment, and get an
approximate p-value--is this the way it works in
fisher.test( ) in R? If not, does it use another test,
or some other measure of approximation?
My last question is: when the group is small enough,
will it calculates the exact probabilities even if
hybrid=F?
Many thanks,
Fang
=====
Lai, Fang
PhD candidate
University of California, Berkeley
Department of Agricultural and Resource Economics
314 Giannini Hall, Berkeley, CA 94720-3310
tel: (510) 643 - 5421(O)
(510) 847 - 9811(Cell)
fax: (510) 643 - 8911
email: [EMAIL PROTECTED]
http://www.are.berkeley.edu/jobmarket/fang.html
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