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Data X:
28.71 180.81 116.35 30.14 164.86 107.25 28.23 161.19 104.58 28.93 153.57 102.93 27.97 157.48 100.74 27.30 151.83 97.57 27.42 143.94 96.42 26.16 144.39 96.48 24.77 142.57 90.53 25.45 140.94 90.81 28.70 149.73 97.17 30.94 167.19 107.55 36.16 194.81 127.10 33.57 175.82 110.68 28.97 159.77 107.16 27.63 163.07 100.57 26.45 148.84 97.58 25.57 145.43 98.27 25.32 150.81 95.19 24.42 146.97 96.06 26.00 140.57 93.77 27.19 150.45 100.29 26.43 153.37 97.27 31.00 175.10 106.55 29.97 180.87 108.87 31.29 173.89 113.21 30.10 166.90 107.90 28.57 167.70 107.47 26.68 150.68 95.94 26.27 149.70 98.37 27.61 145.29 97.55 27.32 148.87 102.03 26.53 152.73 94.77 25.74 154.84 98.42 27.50 159.17 100.83 32.61 186.81 117.45 31.03 187.68 115.39 28.10 162.55 105.41 26.03 158.55 102.26 26.37 153.27 98.00 25.61 142.16 93.55 26.97 146.10 91.00 25.13 142.32 94.48 24.68 137.87 90.29 25.67 141.20 90.97 25.39 149.58 96.19 27.63 151.13 94.87 30.26 170.03 104.58 31.94 176.35 115.61 30.82 185.86 119.43 30.55 185.55 119.55 25.77 157.47 99.00 24.97 149.13 98.94 25.33 148.37 96.37 24.13 133.48 88.42 23.35 133.55 85.45 23.47 138.97 87.90 24.52 148.48 94.45 25.87 147.80 95.13 28.32 167.26 107.10 28.87 176.71 107.52 29.04 168.39 108.96 27.16 168.81 109.65 25.90 153.37 98.00 25.35 147.39 92.19 25.80 147.77 95.07 26.81 163.58 103.52 24.19 136.03 88.42 24.47 140.97 90.57 24.97 139.61 93.94 24.87 148.70 93.33 26.55 156.26 98.42 29.03 167.68 109.29 29.54 179.86 116.07 25.10 159.74 106.29 25.27 156.93 100.33 22.10 144.19 90.23 22.60 143.03 93.00 25.10 135.90 91.74 22.19 135.52 87.45 24.30 139.60 91.13 24.48 149.94 93.94 28.43 161.73 103.57 23.16 157.65 97.58
Names of X columns:
St_BHG St_VG St_WG
Type of Correlation
pearson
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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