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Data X:
1 1 4 0 2 1 1 0 0 2 0 1 4 1 1.5 0 0 0 0 0 1 1 0 1 1 1 1 0 1 2 1 1 0 1 2 0 1 0 1 1 0 1 4 1 2 1 1 1 0 2 0 0 4 0 2 0 1 0 1 0 0 1 2 1 0 0 1 0 0 2 0 0 0 NA NA 1 1 0 1 2 1 1 1 0 2 1 1 0 1 0.5 0 1 0 1 2 0 0 2 1 0 1 1 2 1 2 1 1 1 0 0 0 0 2 NA NA 1 0 0 NA NA 1 1 3 1 2 1 0 0 1 0 1 1 0 NA NA 0 0 0 NA NA 0 0 1 0 2 1 1 0 1 1 1 0 0 0 0.5 1 1 4 0 2 0 0 0 1 0.5 0 0 1 NA NA 0 0 0 1 0.5 1 1 0 NA NA 1 1 4 0 2 0 1 1 1 0 0 1 0 1 1 1 1 4 1 2 1 1 0 1 1 1 1 4 1 2 1 1 0 0 0 1 1 0 1 0.5 0 0 0 1 0 0 1 4 1 2 0 1 0 0 0 1 1 0 0 1 1 1 4 1 2 0 0 4 0 0.5 0 1 0 1 2 1 1 1 1 2 0 1 0 1 2 0 0 4 NA NA 0 1 0 0 0 0 1 2 1 0 0 1 0 1 0.5 0 1 4 NA NA 0 0 4 0 2 0 0 0 NA NA 0 1 0 1 0 1 1 4 1 2 1 1 0 1 1 1 0 0 1 0 0 0 2 1 2 0 1 0 0 1 0 1 0 1 2 0 0 0 0 0 1 1 4 1 1 1 1 4 1 2 0 1 2 0 0 0 1 0 0 0 0 1 0 0 0 0 1 4 0 0 1 1 0 1 2 1 0 0 1 2 0 0 1 1 2 1 1 2 1 2 1 0 0 1 2 1 1 2 1 2 0 0 0 1 2 0 0 4 1 2 0 0 4 1 2 1 0 0 1 2 0 0 0 NA NA 0 0 4 1 2 1 0 0 NA NA 1 1 4 1 2 0 0 2 1 2 0 0 2 NA NA 1 1 0 0 0 1 1 0 1 2 1 1 4 NA NA 0 1 0 1 2 1 1 0 1 2 1 1 0 1 2 1 1 4 1 2 1 1 4 1 2 0 0 0 NA NA 0 0 0 0 0 1 1 2 0 0 0 0 1 1 2 0 0 0 0 0 0 0 2 1 2 0 1 1 0 0
Names of X columns:
pre post1 post2 post3 post4
Type of Correlation


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R Code
panel.tau <- function(x, y, digits=2, prefix='', cex.cor) { usr <- par('usr'); on.exit(par(usr)) par(usr = c(0, 1, 0, 1)) rr <- cor.test(x, y, method=par1) r <- round(rr$p.value,2) txt <- format(c(r, 0.123456789), digits=digits)[1] txt <- paste(prefix, txt, sep='') if(missing(cex.cor)) cex <- 0.5/strwidth(txt) text(0.5, 0.5, txt, cex = cex) } panel.hist <- function(x, ...) { usr <- par('usr'); on.exit(par(usr)) par(usr = c(usr[1:2], 0, 1.5) ) h <- hist(x, plot = FALSE) breaks <- h$breaks; nB <- length(breaks) y <- h$counts; y <- y/max(y) rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...) } bitmap(file='test1.png') pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main) dev.off() load(file='createtable') n <- length(y[,1]) n a<-table.start() a<-table.row.start(a) a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,' ',header=TRUE) for (i in 1:n) { a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE) } a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE) for (j in 1:n) { r <- cor.test(y[i,],y[j,],method=par1) a<-table.element(a,round(r$estimate,3)) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'pair',1,TRUE) a<-table.element(a,'Pearson r',1,TRUE) a<-table.element(a,'Spearman rho',1,TRUE) a<-table.element(a,'Kendall tau',1,TRUE) a<-table.row.end(a) cor.test(y[1,],y[2,],method=par1) for (i in 1:(n-1)) { for (j in (i+1):n) { a<-table.row.start(a) dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='') a<-table.element(a,dum,header=TRUE) rp <- cor.test(y[i,],y[j,],method='pearson') a<-table.element(a,round(rp$estimate,4)) rs <- cor.test(y[i,],y[j,],method='spearman') a<-table.element(a,round(rs$estimate,4)) rk <- cor.test(y[i,],y[j,],method='kendall') a<-table.element(a,round(rk$estimate,4)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-value',header=T) a<-table.element(a,paste('(',round(rp$p.value,4),')',sep='')) a<-table.element(a,paste('(',round(rs$p.value,4),')',sep='')) a<-table.element(a,paste('(',round(rk$p.value,4),')',sep='')) a<-table.row.end(a) } } a<-table.end(a) table.save(a,file='mytable1.tab')

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