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Data X:
166.06 159.81 3.40 154.50 147.75 4.80 146.87 147.13 6.50 145.10 140.33 8.50 143.32 142.87 13.60 137.03 139.67 15.70 132.42 135.35 18.80 130.71 136.32 19.20 128.60 129.27 12.90 130.39 126.81 14.40 138.43 137.17 6.20 154.74 150.94 2.40 184.35 173.71 4.60 163.39 156.68 7.10 149.06 146.84 7.80 147.10 144.17 9.90 138.06 134.81 13.90 134.13 135.13 17.10 139.87 131.45 17.80 133.68 133.77 18.30 125.47 134.87 14.70 137.03 140.90 10.50 140.50 136.57 8.60 157.13 155.52 4.40 159.55 160.16 2.30 160.36 158.04 2.80 156.48 148.42 8.80 153.03 150.70 10.70 138.03 135.26 12.80 139.70 134.63 19.30 138.23 132.23 19.50 145.68 132.55 20.30 139.90 134.13 15.30 142.06 136.94 7.90 145.77 141.73 8.30 171.19 165.68 4.50 171.61 162.48 3.20 150.21 145.86 5.00 144.65 142.19 6.60 140.33 137.30 11.10 129.61 131.71 13.40 130.40 133.67 16.30 128.13 133.81 17.40 125.35 127.48 18.90 129.73 128.10 15.80 136.84 134.32 11.70 137.80 135.83 6.40 153.00 151.87 2.90 165.03 158.87 4.70 172.25 163.86 2.40 177.06 158.58 7.00 142.10 140.13 10.60 136.16 136.87 12.80 135.87 134.20 17.70 119.84 126.19 18.20 119.84 122.52 16.50 126.13 124.20 16.20 133.58 133.87 13.90 132.27 136.53 6.60 153.77 148.90 3.60 161.90 151.19 1.40 155.11 151.29 2.60 156.55 149.06 4.30 138.47 138.80 8.80 130.16 134.77 14.50 133.20 135.43 16.80 152.71 141.19 22.70 121.87 126.77 15.70 129.57 126.43 18.20 127.52 131.00 14.20 132.90 134.00 9.10 143.10 138.13 5.90 154.94 151.06 7.00 166.86 158.61 6.20 147.10 144.03 7.80 142.97 139.57 14.30 127.77 128.74 14.60 131.43 127.20 17.30 126.84 125.90 17.10 123.10 122.06 17.00 127.80 127.23 13.90 133.23 135.13 10.30 148.90 144.83 6.70 143.45 134.94 3.90
Names of X columns:
SVt SMt Tt
Type of Correlation
kendall
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$counts; y <- y/max(y) rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...) } bitmap(file='test1.png') pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main) dev.off() load(file='createtable') n <- length(y[,1]) n a<-table.start() a<-table.row.start(a) a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,' ',header=TRUE) for (i in 1:n) { a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE) } a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE) for (j in 1:n) { r <- cor.test(y[i,],y[j,],method=par1) a<-table.element(a,round(r$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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