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29.82 0.79
3.16 2.21
38.48 2.12
20.82 0.93
0.09 5.38
41.09 3.14
2.97 2.23
0.1 11.88
23.05 9.31
8.46 6.06
9.31 2.31
0.37 6.84
1.32 7.49
154.7 0.72
0.28 4.48
9.4 5.09
11.06 7.44
10.05 1.41
0.06 5.77
0.74 4.84
10.5 2.96
3.83 3.12
2 3.83
198.66 3.11
0.03 2.86
0.41 4.06
7.28 3.32
16.46 1.21
9.85 0.8
0.49 2.52
14.86 1.21
21.7 1.17
34.84 8.17
0.06 5.65
4.53 1.24
12.45 1.46
17.46 4.36
1408.04 3.38
47.7 1.87
0.72 1.03
4.34 1.29
65.7 0.82
4.8 2.84
19.84 1.27
4.31 3.92
11.27 1.95
1.13 4.21
10.66 5.19
5.6 5.51
0.86 2.19
0.07 2.57
10.28 1.53
15.49 2.17
80.72 2.15
6.3 2.07
0.74 3.97
6.13 0.42
1.29 6.86
91.73 1.02
0.88 2.9
5.41 5.87
63.98 5.14
0.24 2.34
0.27 4.73
1.63 2.02
1.79 1.03
4.36 1.58
82.8 5.3
25.37 1.97
11.12 4.38
0.1 2.98
0.46 3.23
15.08 1.89
11.45 1.41
1.66 1.53
0.8 3.07
10.17 0.61
7.94 1.68
9.98 2.92
1236.69 1.16
246.86 1.58
76.42 2.79
32.78 1.88
4.58 5.57
7.64 6.22
60.92 4.61
2.77 1.89
127.25 5.02
7.01 2.1
16.27 5.55
43.18 1.03
24.76 1.17
49 5.69
3.25 8.13
5.47 1.91
6.65 1.22
2.06 6.29
4.65 3.84
2.05 1.66
4.19 1.21
6.16 3.69
3.03 5.83
0.52 15.82
2.11 3.26
22.29 0.99
15.91 0.81
29.24 3.71
14.85 1.53
0.4 2.08
3.8 2.54
1.24 3.46
120.85 2.89
3.51 1.78
2.8 6.08
0.62 3.78
0 7.78
32.52 1.68
25.2 0.87
52.8 1.43
2.26 2.48
0.01 2.94
27.47 0.98
16.71 5.28
0.25 3.58
4.46 5.6
5.99 1.39
17.16 1.56
168.83 1.16
4.99 4.98
3.31 7.52
179.16 0.79
3.8 2.79
7.17 1.91
6.69 4.16
29.99 2.28
96.71 1.1
38.21 4.44
10.6 3.88
2.05 10.8
0.86 3.65
21.76 2.71
143.17 5.69
11.46 0.87
0.05 4.94
0.18 2.45
0.11 3.11
0.19 2.77
0.19 1.49
28.29 5.61
13.73 1.21
9.55 2.7
5.98 1.24
5.3 7.97
5.45 4.06
2.07 5.81
0.55 1.29
10.2 1.24
52.39 3.31
46.76 3.67
21.1 1.32
0.54 4.25
1.23 2.01
9.51 7.25
8 5.79
21.89 1.51
8.01 0.91
47.78 1.32
66.78 2.66
1.11 0.48
6.64 1.13
0.1 2.7
1.34 7.92
10.88 2.34
74 3.33
5.17 5.47
36.35 1.24
45.53 2.84
63.03 4.94
9.206 7.93
317.5 8.22
3.4 2.91
28.54 2.32
29.96 3.57
90.8 1.65
0.01 2.07
23.85 1.03
14.08 0.99
13.72 1.37

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')