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Data X:
21 4 26 9 22 4 22 5 18 4 23 4 12 9 20 8 22 11 21 4 19 4 22 6 15 4 20 8 19 4 18 4 15 11 20 4 21 4 21 6 15 6 16 4 23 8 21 5 18 4 25 9 9 4 30 7 20 10 23 4 16 4 16 7 19 12 25 4 25 7 18 5 23 8 21 5 10 4 14 9 22 7 26 4 23 4 23 4 24 4 24 4 18 7 23 4 15 7 19 4 16 4 25 4 23 4 17 8 19 4 21 4 18 4 27 4 21 7 13 12 8 4 29 4 28 4 23 5 21 15 19 5 19 10 20 9 18 8 19 4 17 5 19 4 25 9 19 4 22 10 23 4 26 7 14 4 28 6 16 7 24 5 20 4 12 4 24 4 22 4 12 4 22 4 20 6 10 10 23 7 17 4 22 4 24 7 18 4 21 8 20 11 20 6 22 14 19 5 20 4 26 8 23 9 24 4 21 4 21 5 19 4 8 5 17 4 20 4 11 7 8 10 15 4 18 5 18 4 19 4 19 4 23 6 22 4 21 8 25 5 30 4 17 17 27 4 23 4 23 8 18 4 18 7 23 4 19 4 15 5 20 7 16 4 24 4 25 7 25 11 19 7 19 4 16 4 19 4 19 4 23 4 21 4 22 6 19 8 20 23 20 4 3 8 23 6 14 4 23 4 20 7 15 4 13 4 16 4 7 4 24 10 17 6 24 5 24 5 19 4 25 4 20 5 28 5 23 5 27 5 18 4 28 6 21 4 19 4 23 4 27 9 22 18 28 6 25 5 21 4 22 11 28 4 20 10 29 6 25 8 25 8 20 6 20 8 16 4 20 4 20 9 23 9 18 5 25 4 18 4 19 15 25 10 25 9 25 7 24 9 19 6 26 4 10 7 17 4 13 7 17 4 30 15 25 4 4 9 16 4 21 4 23 28 22 4 17 4 20 4 20 5 22 4 16 4 23 12 16 5 0 4 18 6 25 6 23 5 12 4 18 4 24 4 11 10 18 7 14 4 23 4 24 7 29 4 18 4 15 12 29 5 16 8 19 6 22 17 16 4 23 5 23 4 19 5 4 5 20 6 24 4 20 4 4 4 24 6 22 8 16 10 3 4 15 5 24 4 17 4 20 4 27 16 23 4 26 7 23 4 17 4 20 14 22 5 19 5 24 5 19 5 23 7 15 19 27 16 26 4 22 4 22 7 18 9 15 5 22 14 27 4 10 16 20 10 17 5 23 6 19 4 13 4 27 4 23 5 16 4 25 4 2 5 26 4 20 4 23 5 22 8 24 15
Names of X columns:
NUMERACYTOT AMS.A
Type of Correlation
pearson
pearson
spearman
kendall
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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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