Preparing a paper for a medical journal.
Using the prop.test() function in R (v2.4.0)
to compare two groups' response to data like the following.
A sample of 100 individuals from Population I, 18 with positive readings
from a certain test,
vs.
A sample of 148 individuals from Population II, 61 with positive readings.
Results look like this:
R version 2.4.0 Patched (2006-11-25 r39997)
......
> prop.test(c(18,61),c(100,148))
2-sample test for equality of proportions with continuity
correction
data: c(18, 61) out of c(100, 148)
X-squared = 13.7676, df = 1, p-value = 0.0002069
alternative hypothesis: two.sided
95 percent confidence interval:
-0.3498963 -0.1144280
sample estimates:
prop 1 prop 2
0.1800000 0.4121622
Presumably the p-value measures that the likelihood
that the two populations have the same proportion of
response. My question is this. The reviewer of the
paper has asked for a reference on the algorithm used
to compute the p-value. The R Reference Manual is not
clear on this. Is this a standard algorithm that can
be quoted by name (e.g., "Two-sample T Test")? I
do note that the manual quotes a 1927 article by E.B.
Wilson. Is the method of computation explained there?
Thank you for any assistance you can provide.
George Heine
ghe...@mathnmaps.com
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