mercuryfish {coin} | R Documentation |
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.
data(mercuryfish)
A data frame with 39 observations on the following 4 variables.
control
and exposed
.
Subjects who ate contaminated fish for more than three years in the
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 (mercury
,
abnormal
and 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).
S. Skerfving, K. Hansson, C. Mangs, J. Lindsten, N. Ryman (1974), Methylmercury-induced chromosome damage in men. Environmental Research, 7, 83–98.
P. R. Rosenbaum (1994), Coherence in Observational Studies. Biometrics, 50, 368–374.
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)