Perform Fisher Exact Test from aggregated using Stata - stata

Question

I have a set of data like below:
A B C D
1 2 3 4
2 3 4 5
They are aggregated data which ABCD constitutes a 2x2 table, and I need to do Fisher exact test on each row, and add a new column for the p-value of the Fisher exact test for that row.
I can use fisher.exact and loop to do it in R, but I can't find a command in Stata for Fisher exact test.

Answer 1

You are thinking in R terms, and that is often fruitless in Stata (just as it is impossible for a Stata guy to figure out how to do by ... : regress in R; every package has its own paradigm and its own strengths).
There are no objects to add columns to. May be you could say a little bit more as to what you need to do, eventually, with your p-values, so as to find an appropriate solution that your Stata collaborators would sympathize with.
If you really want to add a new column (generate a new variable, speaking Stata), then you might want to look at tabulate and its returned values:
clear
input x y f1 f2
0 0 5 10
0 1 7 12
1 0 3 8
1 1 9 5
end
I assume that your A B C D stand for two binary variables, and the numbers are frequencies in the data. You have to clear the memory, as Stata thinks about one data set at a time.
Then you could tabulate the results and generate new variables containing p-values, although that would be a major waste of memory to create variables that contain a constant value:
tabulate x y [fw=f1], exact
return list
generate p1 = r(p_exact)
tabulate x y [fw=f2], exact
generate p2 = r(p_exact)
Here, [fw=variable] is a way to specify frequency weights; I typed return list to find out what kind of information Stata stores as the result of the procedure. THAT'S the object-like thing Stata works with. R would return the test results in the fisher.test()$p.value component, and Stata creates returned values, r(component) for simple commands and e(component) for estimation commands.
If you want a loop solution (if you have many sets), you can do this:
forvalues k=1/2 {
tabulate x y [fw=f`k'], exact
generate p`k' = r(p_exact)
}
That's the scripting capacity in which Stata, IMHO, is way stronger than R (although it can be argued that this is an extremely dirty programming trick). The local macro k takes values from 1 to 2, and this macro is substituted as ``k'` everywhere in the curly bracketed piece of code.
Alternatively, you can keep the results in Stata short term memory as scalars:
tabulate x y [fw=f1], exact
scalar p1 = r(p_exact)
tabulate x y [fw=f2], exact
scalar p2 = r(p_exact)
However, the scalars are not associated with the data set, so you cannot save them with the
data.
The immediate commands like cci suggested here would also have returned values that you can similarly retrieve.
HTH, Stas

Answer 2

Have a look the cci command with the exact option:
cci 10 15 30 10, exact
It is part of the so-called "immediate" commands. They allow you to do computations directly from the arguments rather than from data stored in memory. Have a look at help immediate

Answer 3

Each observation in the poster's original question apparently consisted of the four counts in one traditional 2 x 2 table. Stas's code applied to data of individual observations. Nick pointed out that -cci- can analyze a b c d data. Here's code that applies -cci to each table and, like Stas's code, adds the p-values to the data set. The forvalues i = 1/`=_N' statement tells Stata to run the loop from the first to the last observation. a[`i'] refers to the the value of the variable `a' in the i-th observation.
clear
input a b c d
10 2 8 4
5 8 2 1
end
gen exactp1 = .
gen exactp2 =.
label var exactp1 "1-sided exact p"
label var exactp2 "2-sided exact p"
forvalues i = 1/`=_N'{
local a = a[`i']
local b = b[`i']
local c = c[`i']
local d = d[`i']
qui cci `a' `b' `c' `d', exact
replace exactp1 = r(p1_exact) in `i'
replace exactp2 = r(p_exact) in `i'
}
list
Note that there is no problem in giving a local macro the same name as a variable.