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Data X:
19 13 19 5 0 23 15 21 4 0 6 4 22 5 0 6 12 21 3 0 7 21 19 2 0 18 19 21 1 0 3 0 19 2 0 7 8 20 1 0 20 20 21 2 0 9 12 22 4 0 11 16 23 5 0 7 10 21 5 1 25 19 22 4 0 4 11 19 3 0 35 19 20 5 0 13 12 18 1 0 18 11 21 4 0 6 14 21 2 0 8 10 19 2 0 12 1 19 2 1 20 18 24 1 0 4 22 18 6 0 11 13 18 2 0 32 20 23 2 0 2 4 19 2 0 22 16 20 4 0 2 2 19 2 0 2 2 21 6 0 9 9 20 2 0 32 19 19 3 0 3 6 19 1 0 10 9 23 6 0 5 6 21 4 0 24 18 20 3 0 10 12 21 3 0 10 11 22 6 1 19 12 21 3 0 2 1 23 4 0 16 10 21 6 0 11 26 19 4 0 28 15 23 3 0 20 13 24 7 0 18 12 24 4 0 9 14 21 3 0 0 5 18 0 0 10 12 22 2 0 20 29 19 2 0 11 10 20 2 1 12 10 22 3 0 8 19 20 4 0 12 9 23 5 0 21 13 21 4 0 11 11 21 2 0 28 24 21 3 0 4 7 20 2 0 38 22 19 2 1 8 7 23 5 0 7 8 21 4 0 4 6 18 1 0 15 11 23 6 0 12 12 18 1 0 3 3 19 3 0 8 12 18 5 0 3 0 21 2 0 24 22 22 4 0 23 14 23 5 0 17 12 18 1 0 22 17 23 4 0 23 12 24 6 0 12 11 23 5 0 6 8 19 2 0 34 23 20 3 0 5 15 20 4 0 21 13 22 3 0 13 24 21 2 0 4 5 24 3 0 8 17 23 4 1 20 11 21 4 0 17 10 20 4 0 11 19 23 4 0 23 25 23 3 0 7 28 23 3 0 5 2 23 3 0 25 12 24 4 0 12 25 20 2 0 6 7 20 1 0 21 17 22 5 0 28 26 23 2 0 7 5 23 5 0 21 11 19 3 0 5 13 20 3 0 22 21 20 2 0 7 6 21 3 0 3 6 21 3 0 7 8 22 4 0 13 14 18 2 0 15 12 24 5 0 26 20 20 6 0 18 10 24 5 0 4 7 19 1 1 19 14 22 4 1 16 33 22 3 0 12 21 21 2 1 10 14 18 1 0 23 12 20 2 0 6 9 23 3 0 16 15 19 3 0 10 24 22 3 0 3 0 22 4 0 2 7 19 2 0 17 12 24 6 0 6 11 19 2 0 19 12 19 4 0 6 5 24 4 0 10 9 20 2 0 6 18 21 3 0 3 2 20 2 0 11 11 20 2 0 18 10 19 1 0 4 6 21 2 0 6 12 21 3 0 29 31 21 3 0 12 16 18 2 0 7 22 20 2 0 8 35 20 1 0 30 23 23 6 0
Names of X columns:
MajorHR MinorHR Age YearsPro Right/Left
Type of Correlation
0.3
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$counts; y <- y/max(y) rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...) } x <- na.omit(x) y <- t(na.omit(t(y))) bitmap(file='test1.png') pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main) dev.off() load(file='createtable') n <- length(y[,1]) print(n) a<-table.start() a<-table.row.start(a) a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,' ',header=TRUE) for (i in 1:n) { a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE) } a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE) for (j in 1:n) { r <- cor.test(y[i,],y[j,],method=par1) a<-table.element(a,round(r$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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