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Data X:
325.87 5.70 302.25 3.40 294.00 4.80 285.43 6.50 286.19 8.50 276.70 13.60 267.77 15.70 267.03 18.80 257.87 19.20 257.19 12.90 275.60 14.40 305.68 6.20 358.06 2.40 320.07 4.60 295.90 7.10 291.27 7.80 272.87 9.90 269.27 13.90 271.32 17.10 267.45 17.80 260.33 18.30 277.94 14.70 277.07 10.50 312.65 8.60 319.71 4.40 318.39 2.30 304.90 2.80 303.73 8.80 273.29 10.70 274.33 12.80 270.45 19.30 278.23 19.50 274.03 20.30 279.00 15.30 287.50 7.90 336.87 8.30 334.10 4.50 296.07 3.20 286.84 5.00 277.63 6.60 261.32 11.10 264.07 13.40 261.94 16.30 252.84 17.40 257.83 18.90 271.16 15.80 273.63 11.70 304.87 6.40 323.90 2.90 336.11 4.70 335.65 2.40 282.23 7.00 273.03 10.60 270.07 12.80 246.03 17.70 242.35 18.20 250.33 16.50 267.45 16.20 268.80 13.90 302.68 6.60 313.10 3.60 306.39 1.40 305.61 2.60 277.27 4.30 264.94 8.80 268.63 14.50 293.90 16.80 248.65 22.70 256.00 15.70 258.52 18.20 266.90 14.20 281.23 9.10 306.00 5.90 325.46 7.00 291.13 6.20 282.53 7.80 256.52 14.30 258.63 14.60 252.74 17.30 245.16 17.10 255.03 17.00 268.35 13.90 293.73 10.30 278.39 6.70
Names of X columns:
St T-1
Type of Correlation
pearson
spearman
kendall
Chart options
Title:
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$counts; y <- y/max(y) rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...) } x <- na.omit(x) y <- t(na.omit(t(y))) bitmap(file='test1.png') pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main) dev.off() load(file='createtable') n <- length(y[,1]) n a<-table.start() a<-table.row.start(a) a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,' ',header=TRUE) for (i in 1:n) { a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE) } a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE) for (j in 1:n) { r <- cor.test(y[i,],y[j,],method=par1) a<-table.element(a,round(r$estimate,3)) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') ncorrs <- (n*n -n)/2 mycorrs <- array(0, dim=c(10,3)) 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) for (iii in 1:10) { iiid100 <- iii / 100 if (rp$p.value < iiid100) mycorrs[iii, 1] = mycorrs[iii, 1] + 1 if (rs$p.value < iiid100) mycorrs[iii, 2] = mycorrs[iii, 2] + 1 if (rk$p.value < iiid100) mycorrs[iii, 3] = mycorrs[iii, 3] + 1 } } } a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Meta Analysis of Correlation Tests',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Number of significant by total number of Correlations',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Type I error',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) for (iii in 1:10) { iiid100 <- iii / 100 a<-table.row.start(a) a<-table.element(a,round(iiid100,2),header=T) a<-table.element(a,round(mycorrs[iii,1]/ncorrs,2)) a<-table.element(a,round(mycorrs[iii,2]/ncorrs,2)) a<-table.element(a,round(mycorrs[iii,3]/ncorrs,2)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable2.tab')
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