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30 26.56
17 20.16
24 30.24
20 18.56
25 23.36
20 22.16
27 23.76
18 18.8
28 29.52
21 25.44
27 31.84
22 17.52
28 29.52
25 24.16
21 24
22 18.16
28 25.52
20 28.96
29 23.36
20 28.16
20 24.56
23 21.44
18 22.24
18 24.4
19 20.64
25 25.76
25 27.76
25 21.04
24 19.44
19 20.16
26 16.56
10 24.64
17 15.36
13 29.12
17 21.76
30 23.76
4 22.56
16 23.84
21 26
22 21.76
20 25.04
22 23.36
23 20.24
16 19.04
0 30.72
18 26.56
25 17.92
18 21.12
18 25.36
24 17.84
29 25.04
15 12.24
22 24.32
23 24.96
24 20.96
22 18.96
15 19.84
17 18.24
20 23.84
27 31.84
26 17.92
23 23.36
23 23.6
15 24.24
26 26.96
22 12.56
18 20.16
15 12.56
22 17.52
27 19.76
10 15.92
20 23.84
17 26.64
23 21.44
19 22.32
13 25.12
27 26.96
23 17.52
16 24.56
25 19.52
2 24.16
26 28.4
20 24.32
22 26.64
24 12.96
23 6.96
22 20.32
21 28.96
25 28.56
27 27.36
23 30.56
23 25.76
18 21.36
18 29.44
23 23.52
19 16.96
15 20.16
20 25.92
16 21.76
25 22.56
25 23.2
19 25.84
19 23.6
16 23.68
19 19.92
19 20.24
23 27.76
21 13.76
22 29.44
19 25.76
20 28.4
3 24.4
23 28.24
14 24.96
23 26.16
20 28.24
15 21.76
13 18.72
16 22.96
7 23.6
24 29.2
17 15.84
24 25.6
24 29.2
19 26.96
28 30.32
23 24.96
19 27.36
23 25.76
25 24.64
25 24.64
20 21.36
16 30.56
20 12.16
25 30.56
25 23.6
23 30.8
17 21.76
20 20.4
16 15.76
23 24.4
12 19.04
24 26.16
11 19.84
14 22.96
23 29.04
18 28.4
29 19.76
16 24.96
19 30.88
16 27.36
23 29.44
19 30.48
4 29.68
20 30.56
20 20.56
4 15.2
24 7.2
16 21.76
3 18.72
24 21.36
23 28.4
17 28.16
20 22.48
22 25.76
19 21.36
24 18.96
19 19.12
27 21.12
22 12.32
23 23.36

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')