swh:1:snp:813359ba77493c9d5dd1abad9a1f53490a8abf57
Tip revision: 891d3973285d3cd5421a5921add474c92000b605 authored by Torsten Hothorn on 02 June 2005, 00:00:00 UTC
version 0.2-11
version 0.2-11
Tip revision: 891d397
mercuryfish.Rd
\name{mercuryfish}
\alias{mercuryfish}
\docType{data}
\title{ Chromosomal effects of mercury contaminated fish consumption }
\description{
The mercury level in the blood, the proportion of cells with
abnormalities and the proportion of cells with chromosome aberrations
for a group of consuments of mercury contaminated fish and a control
group.
}
\usage{data(mercuryfish)}
\format{
A data frame with 39 observations on the following 4 variables.
\describe{
\item{group}{a factor with levels \code{control} and \code{exposed}.}
\item{mercury}{the level of mercury in the blood.}
\item{abnormal}{the proportion of cells with structural abnormalities.}
\item{ccells}{the proportion of cells with asymmetrical or
incomplete-symmetrical chomosome aberrations called
\eqn{C_u} cells.}
}
}
\details{
Subjects who ate contaminated fish for more than three years in the
\code{exposed} group and subjects of a control group are to be compared.
Instead of a multivariate comparison, Rosenbaum (1994)
applied a coherence criterion. The observations are partially ordered: an
observation is than another when all three variables (\code{mercury},
\code{abnormal} and \code{ccells}) are smaller and a score reflecting the
`ranking' is attached to each observation. The distribution of the scores
in both groups is to be compared and the corresponding test is called
`POSET-test' (partially ordered sets).
}
\source{
S. Skerfving, K. Hansson, C. Mangs, J. Lindsten, N. Ryman (1974),
Methylmercury-induced chromosome damage in men.
\emph{Environmental Research}, \bold{7}, 83--98.
}
\references{
P. R. Rosenbaum (1994), Coherence in Observational Studies.
\emph{Biometrics}, \bold{50}, 368--374.
}
\examples{
data(mercuryfish)
coherence <- function(data) {
x <- as.matrix(data)
matrix(apply(x, 1, function(y)
sum(colSums(t(x) < y) == ncol(x)) -
sum(colSums(t(x) > y) == ncol(x))), ncol = 1)
}
### POSET-test
poset <- independence_test(mercury + abnormal + ccells ~ group, data =
mercuryfish, ytrafo = coherence)
### linear statistic (T in Rosenbaum's, 1994, notation)
statistic(poset, "linear")
### expectation
expectation(poset)
### variance (Rosenbaum, 1994, uses the unconditional approach)
covariance(poset)
### the standardized statistic
statistic(poset)
### and asymptotic p-value
pvalue(poset)
### exact p-value
independence_test(mercury + abnormal + ccells ~ group, data =
mercuryfish, ytrafo = coherence, distribution = "exact")
### multivariate analysis
mvtest <- independence_test(mercury + abnormal + ccells ~ group,
data = mercuryfish)
### global p-value
pvalue(mvtest)
### adjusted univariate p-value
pvalue(mvtest, adjusted = TRUE)
}
\keyword{datasets}