On Dec 12, 2008, at 8:57 AM, Peter Dalgaard wrote:
Chuck Cleland wrote:
On 12/12/2008 3:29 AM, robert-mcfad...@o2.pl wrote:
Hello,
Which package allows to use Cochrana-Armitage trend test? I tried
to search for but I found only package coin in which there is no
explicit function.
But there is this example in coin:
### Cochran-Armitage trend test for proportions
### Lung tumors in female mice exposed to 1,2-dichloroethane
### Encyclopedia of Biostatistics (Armitage & Colton, 1998),
### Chapter Trend Test for Counts and Proportions, page 4578, Table 2
lungtumor <- data.frame(dose = rep(c(0, 1, 2), c(40, 50, 48)),
tumor = c(rep(c(0, 1), c(38, 2)),
rep(c(0, 1), c(43, 7)),
rep(c(0, 1), c(33, 15))))
table(lungtumor$dose, lungtumor$tumor)
### Cochran-Armitage test (permutation equivalent to correlation
### between dose and tumor), cf. Table 2 for results
independence_test(tumor ~ dose, data = lungtumor, teststat = "quad")
See the following:
http://finzi.psych.upenn.edu/R/library/coin/html/
ContingencyTests.html
Also prop.trend.test().
There seems to be a subtle difference, though:
independence_test(tumor ~ dose, data = lungtumor, teststat = "quad")
Asymptotic General Independence Test
data: tumor by dose
chi-squared = 10.6381, df = 1, p-value = 0.001108
tt <- table(lungtumor$dose, lungtumor$tumor)
prop.trend.test(tt[,2],rowSums(tt))
Chi-squared Test for Trend in Proportions
data: tt[, 2] out of rowSums(tt) ,
using scores: 1 2 3
X-squared = 10.7157, df = 1, p-value = 0.001062
Anyone have a guess at what the difference is? (Just curious.)
My guess is that this is the difference between a rank-correlation
test and a score based linear correlation test. I just looked at
chapter 13 of "Medical Uses of Statistics" in which Moses, Emerson and
Hosseini describe using a Wilcoxon statistic to tackle this problem.
That appears to be equivalent to the permutation method implemented in
the independence_test(). The authors of coin call it an equivalent
rather than a "faithful" implemention.
My examination of the Armitage formula in his "Statistical Methods in
Medical Research" (which appears to be what you implemented in
prop.trend.test) did not lead me to think it was a rank or permutation
based method.
I don't have JSTOR access, but if you do, a relevant citation for the
permutation method appears to be:
<http://www.jstor.org/pss/2530667>
--
David Winsemius, MD
Heritage Labs
-pd
There also is an implementation in the GeneticsBase package
(Bioconductor).
Best,
RobMac
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--
O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B
c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
(*) \(*) -- University of Copenhagen Denmark Ph: (+45)
35327918
~~~~~~~~~~ - (p.dalga...@biostat.ku.dk) FAX: (+45)
35327907
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