\name{CADM.global}
+\alias{CADM}
\alias{CADM.global}
\alias{CADM.post}
\title{ Congruence among distance matrices }
Use in phylogenetic analysis: to identify congruence among distance matrices (D) representing different genes or different types of data. Congruent D matrices correspond to data tables that can be used together in a combined phylogenetic or other type of multivariate analysis.
}
\usage{
-CADM.global(Dmat, nmat, n, nperm=99, make.sym=TRUE, weights=NULL, silent=FALSE)
-CADM.post (Dmat, nmat, n, nperm=99, make.sym=TRUE, weights=NULL, mult="holm", mantel=FALSE, silent=FALSE)
+CADM.global(Dmat, nmat, n, nperm=99, make.sym=TRUE, weights=NULL,
+ silent=FALSE)
+CADM.post (Dmat, nmat, n, nperm=99, make.sym=TRUE, weights=NULL,
+ mult="holm", mantel=FALSE, silent=FALSE)
}
\arguments{
The Holm correction is computed after ordering the P-values in a list with the smallest value to the left. Compute adjusted P-values as:
-\eqn{P_corr = (k-i+1)*P}
+\deqn{P_{corr} = (k-i+1)*P}{P_corr = (k-i+1)*P}
-where i is the position in the ordered list. Final step: from left to right, if an adjusted P_corr in the ordered list is smaller than the one occurring at its left, make the smallest one equal to the largest one.
+where i is the position in the ordered list. Final step: from left to right, if an adjusted \eqn{P_{corr}}{P_corr} in the ordered list is smaller than the one occurring at its left, make the smallest one equal to the largest one.
The Sidak correction is:
-\eqn{P_corr = 1 - (1 - P)^k}
+\deqn{P_{corr} = 1 - (1 - P)^k}{P_corr = 1 - (1 - P)^k}
The Bonferonni correction is:
-\eqn{P_corr = k*P}
+\deqn{P_{corr} = k*P}{P_corr = k*P}
}
\value{
-\code{CADM.global} produces a small table containing the W, Chi2, and Prob.perm statistics described in the following list.
-\code{CADM.post} produces a table stored in element $A_posteriori_tests, containing Mantel.mean, Prob, and Corrected.prob statistics in rows; the columns correspond to the k distance matrices under study, labeled Dmat.1 to Dmat.k.
+\code{CADM.global} produces a small table containing the W, Chi2, and Prob.perm statistics described in the following list.
+\code{CADM.post} produces a table stored in element \code{A_posteriori_tests}, containing Mantel.mean, Prob, and Corrected.prob statistics in rows; the columns correspond to the k distance matrices under study, labeled Dmat.1 to Dmat.k.
If parameter \code{mantel} is TRUE, tables of Mantel statistics and P-values are computed among the matrices.
- \item{W }{Kendall's coefficient of concordance, W (Kendall and Babington Smith 1939). }
+ \item{W }{Kendall's coefficient of concordance, W (Kendall and Babington Smith 1939; see also Legendre 2010). }
\item{Chi2 }{Friedman's chi-square statistic (Friedman 1937) used in the permutation test of W. }
\item{Prob.perm }{Permutational probability. }
}
\references{
-Campbell, V., P. Legendre and F.-J. Lapointe. 2009. Assessing congruence among ultrametric distance matrices. Journal of Classification (In press).
+Campbell, V., P. Legendre and F.-J. Lapointe. 2009. Assessing congruence among ultrametric distance matrices. Journal of Classification 26: 103-117.
-Campbell, V., P. Legendre and F.-J. Lapointe. Performance of the congruence test among distance matrices in phylogenetic analysis. (Submitted MS).
+Campbell, V., P. Legendre and F.-J. Lapointe. 2011. The performance of the Congruence Among Distance Matrices (CADM) test in phylogenetic analysis. BMC Evolutionary Biology 11: 64. http://www.biomedcentral.com/1471-2148/11/64.
Friedman, M. 1937. The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association 32: 675-701.
Lapointe, F.-J., J. A. W. Kirsch and J. M. Hutcheon. 1999. Total evidence, consensus, and bat phylogeny: a distance-based approach. Molecular Phylogenetics and Evolution 11: 55-66.
-Legendre, P. 2008. Coefficient of concordance. In: Encyclopedia of Research Design. SAGE Publications (in press).
+Legendre, P. 2010. Coefficient of concordance. Pp. 164-169 in: Encyclopedia of Research Design, Vol. 1. N. J. Salkind, ed. SAGE Publications, Inc., Los Angeles.
Legendre, P. and F.-J. Lapointe. 2004. Assessing congruence among distance matrices: single malt Scotch whiskies revisited. Australian and New Zealand Journal of Statistics 46: 615-629.
Siegel, S. and N. J. Castellan, Jr. 1988. Nonparametric statistics for the behavioral sciences. 2nd edition. McGraw-Hill, New York.
}
-\seealso{ \code{\link{kendall.W}}, \code{\link[ape:ape-package]{ape}} }
+
\author{ Pierre Legendre, Universite de Montreal }
\examples{
# identical evolutionary parameters (GTR+ Gamma + I). Distance matrices were
# computed from the DNA sequence matrices using a p distance corrected with the
# same parameters as those used to simulate the DNA sequences. See Campbell et
-# al. (submitted) for details.
+# al. (2009) for details.
-# First example: five independent additive trees. Data provided by V. Campbell.
+# Example 1: five independent additive trees. Data provided by V. Campbell.
data(mat5Mrand)
res.global <- CADM.global(mat5Mrand, 5, 50)
-# Second example: three partly similar trees, two independent trees.
+# Example 2: three partly similar trees, two independent trees.
# Data provided by V. Campbell.
data(mat5M3ID)
res.global <- CADM.global(mat5M3ID, 5, 50)
res.post <- CADM.post(mat5M3ID, 5, 50, mantel=TRUE)
-# Third example: three matrices respectively representing Serological
+# Example 3: three matrices respectively representing Serological
# (asymmetric), DNA hybridization (asymmetric) and Anatomical (symmetric)
# distances among 9 families. Data from Lapointe et al. (1999).
data(mat3)
res.global <- CADM.global(mat3, 3, 9, nperm=999)
res.post <- CADM.post(mat3, 3, 9, nperm=999, mantel=TRUE)
+
+# Example 4, showing how to bind two D matrices (cophenetic matrices
+# in this example) into a file using rbind(), then run the global test.
+
+a <- rtree(5)
+b <- rtree(5)
+A <- cophenetic(a)
+B <- cophenetic(b)
+x <- rownames(A)
+B <- B[x, x]
+M <- rbind(A, B)
+CADM.global(M, 2, 5)
}
\keyword{ multivariate }
projects / ape.git / blobdiff