FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationThu, 15 Jan 2015 09:46:09 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Jan/15/t1421315183uk7vivnc4nxvoyx.htm/, Retrieved Thu, 16 May 2024 01:02:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=272542, Retrieved Thu, 16 May 2024 01:02:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact84

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Survey Scores] [Intrinsic Motivat...] [2010-10-12 11:18:40] [b98453cac15ba1066b407e146608df68]
- RMP   [Survey Scores] [] [2014-10-09 22:08:50] [32b17a345b130fdf5cc88718ed94a974]
-    D    [Survey Scores] [P IM kwal-kwan] [2014-12-10 19:22:20] [46c7ebd23dbdec306a09830d8b7528e7]
-    D      [Survey Scores] [P IM2 kwal-kwan] [2014-12-12 18:04:48] [46c7ebd23dbdec306a09830d8b7528e7]
- RMP           [Kendall tau Correlation Matrix] [kgkigkj] [2015-01-15 09:46:09] [9772ee27deeac3d50cc1fb84835cd7d6] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2 2 2 2
5 4 4 5
4 4 5 5
3 3 3 3
7 6 6 5
3 4 5 4
5 5 5 4
5 5 1 5
4 4 4 3
7 7 7 7
5 5 6 5
3 5 5 5
6 5 6 5
2 5 6 6
5 5 6 6
5 6 7 7
4 5 6 5
4 4 5 3
5 5 4 5
5 4 4 5
6 7 6 7
6 6 5 7
5 5 5 5
5 4 5 5
3 5 6 5
6 6 5 6
5 5 4 4
4 5 3 4
4 5 4 5
4 6 6 5
4 5 5 6
3 5 5 2
5 5 5 4
7 6 7 7
4 5 6 4
2 1 2 2
3 5 6 6
5 5 5 5
5 6 3 5
5 4 6 4
5 5 5 5
4 3 4 7
4 3 5 2
3 4 5 5
4 4 4 5
2 2 2 2
2 3 2 2
5 5 6 6
5 5 5 5
5 6 5 4
4 6 6 6
6 5 6 5
5 5 6 6
2 4 5 5
4 2 3 5
6 6 6 6
5 5 6 5
5 5 5 5
2 6 6 6
3 6 5 4
3 5 3 3
5 5 5 4
7 6 6 5
4 3 6 6
2 3 6 5
2 4 5 5
4 5 5 2
4 4 3 3
5 5 6 6
4 4 7 6
4 5 4 2
3 3 5 3
4 3 5 3
3 2 4 5
6 5 4 5
6 5 5 5
3 3 6 5
2 2 4 6
5 5 4 5
2 4 5 5
4 3 3 3
7 6 7 6
3 3 5 2
4 4 5 5
4 4 3 4
4 4 5 5
6 5 6 4
3 4 5 5
5 4 6 3
5 5 5 5
4 5 4 5
6 7 6 6
4 5 5 6
4 4 6 5
4 4 5 5
3 3 3 3
4 5 7 6
2 5 4 5
4 5 5 4
5 6 6 6
4 5 6 5
4 5 6 5
4 4 4 4
6 6 4 6
4 5 5 5
5 7 6 5
1 2 2 1
4 4 6 5
5 6 6 7
5 4 5 5
2 4 4 5
3 5 6 4
5 4 4 5
5 6 6 5
5 6 6 6
1 6 5 6
4 5 4 4
2 2 1 1
3 5 7 7
5 5 5 5
3 4 5 4
4 6 3 3
5 4 4 4
6 6 4 4
5 6 5 7
5 4 4 5
5 3 2 3
6 6 5 5
5 5 5 5
5 5 5 5
2 4 3 4
4 7 4 1
7 7 6 5
4 5 3 4
2 4 5 4
5 5 4 5
6 5 4 4
6 6 6 6
2 2 2 3
5 6 5 6
3 4 4 4
4 6 6 6
5 5 6 6
6 6 5 7
3 2 3 4
2 6 7 6
6 6 6 7
7 7 6 6
5 6 5 3
5 5 6 5
3 4 3 4
7 7 7 7
4 4 4 4
5 5 6 5
5 5 3 3
4 3 4 5
6 7 6 6
4 6 5 6
6 5 6 5
3 3 1 2
5 5 5 5
4 6 5 4
7 7 3 7
4 6 6 6
5 5 6 6
1 4 2 5
4 3 5 5
4 5 4 5
2 2 5 1
5 6 6 5
6 7 6 5
3 6 6 3
4 5 4 5
6 5 6 6
4 6 6 5
5 6 5 5
7 7 7 7
4 5 4 4
4 5 6 6
5 5 6 5
5 5 5 5
4 5 4 5
3 4 5 5
1 2 2 2
4 5 5 3
4 4 2 4
4 5 5 4
5 4 2 3
5 6 6 6
5 5 5 5
2 3 5 4
4 6 2 5
6 6 5 4
6 6 6 5
6 6 6 6
4 6 6 5
3 4 4 3
6 6 6 6
3 3 5 5
6 6 4 5
1 4 2 1
5 3 5 4
3 5 6 4
4 4 5 4
4 2 5 5
5 5 6 6
4 5 6 2
5 6 5 5
5 4 6 5
5 5 4 6
3 5 6 5
2 1 1 4
5 3 5 6
2 4 2 3
2 3 4 6
3 4 3 3
3 5 5 5
5 5 5 4
6 6 6 5
4 4 6 6
5 7 5 5
4 5 5 5
3 4 5 4
3 2 3 3
4 2 3 2
6 5 5 5
3 3 4 4
5 6 5 5
5 5 4 6
5 5 6 5
4 5 5 6
4 4 5 6
5 5 4 5
4 4 5 5
4 5 6 5
5 5 5 6
5 6 6 5
4 6 4 5
6 6 6 5
4 3 3 6
5 6 6 6
3 5 5 5
5 6 6 6
5 5 5 5
5 5 5 5
6 7 5 5
2 7 2 2
3 6 6 6
7 7 7 5
2 6 5 5
4 6 5 4
5 6 3 4
5 5 6 3
3 6 6 3
6 6 3 4
4 3 3 3
2 3 2 3
5 6 4 6
7 6 6 5
6 5 4 6
6 6 6 5
3 5 5 5
2 3 5 1
4 5 4 3
6 4 4 6
4 5 5 6
6 7 7 6
3 6 7 5
2 4 2 4
3 5 3 4
3 4 6 5
4 3 3 4
4 5 4 5
2 5 4 5
6 5 5 3
2 3 1 1
6 1 7 7
6 6 6 6
5 5 6 5
5 5 5 5
3 7 5 7
4 5 4 4
4 5 6 4
5 5 5 5
3 5 4 4
5 5 5 5
3 5 4 4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=272542&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=272542&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=272542&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Correlations for all pairs of data series (method=pearson)
AMS6AMS13AMS20AMS27
AMS610.5420.4230.453
AMS130.54210.4830.443
AMS200.4230.48310.554
AMS270.4530.4430.5541

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & AMS6 & AMS13 & AMS20 & AMS27 \tabularnewline
AMS6 & 1 & 0.542 & 0.423 & 0.453 \tabularnewline
AMS13 & 0.542 & 1 & 0.483 & 0.443 \tabularnewline
AMS20 & 0.423 & 0.483 & 1 & 0.554 \tabularnewline
AMS27 & 0.453 & 0.443 & 0.554 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=272542&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]AMS6[/C][C]AMS13[/C][C]AMS20[/C][C]AMS27[/C][/ROW]
[ROW][C]AMS6[/C][C]1[/C][C]0.542[/C][C]0.423[/C][C]0.453[/C][/ROW]
[ROW][C]AMS13[/C][C]0.542[/C][C]1[/C][C]0.483[/C][C]0.443[/C][/ROW]
[ROW][C]AMS20[/C][C]0.423[/C][C]0.483[/C][C]1[/C][C]0.554[/C][/ROW]
[ROW][C]AMS27[/C][C]0.453[/C][C]0.443[/C][C]0.554[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=272542&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=272542&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series (method=pearson)
AMS6AMS13AMS20AMS27
AMS610.5420.4230.453
AMS130.54210.4830.443
AMS200.4230.48310.554
AMS270.4530.4430.5541






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
AMS6;AMS130.5420.5350.4607
p-value(0)(0)(0)
AMS6;AMS200.42320.36990.3113
p-value(0)(0)(0)
AMS6;AMS270.45250.41390.3478
p-value(0)(0)(0)
AMS13;AMS200.48280.45750.3911
p-value(0)(0)(0)
AMS13;AMS270.44270.42720.37
p-value(0)(0)(0)
AMS20;AMS270.55390.52150.4496
p-value(0)(0)(0)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
AMS6;AMS13 & 0.542 & 0.535 & 0.4607 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
AMS6;AMS20 & 0.4232 & 0.3699 & 0.3113 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
AMS6;AMS27 & 0.4525 & 0.4139 & 0.3478 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
AMS13;AMS20 & 0.4828 & 0.4575 & 0.3911 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
AMS13;AMS27 & 0.4427 & 0.4272 & 0.37 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
AMS20;AMS27 & 0.5539 & 0.5215 & 0.4496 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=272542&T=2

[TABLE]
[ROW][C]Correlations for all pairs of data series with p-values[/C][/ROW]
[ROW][C]pair[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]AMS6;AMS13[/C][C]0.542[/C][C]0.535[/C][C]0.4607[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]AMS6;AMS20[/C][C]0.4232[/C][C]0.3699[/C][C]0.3113[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]AMS6;AMS27[/C][C]0.4525[/C][C]0.4139[/C][C]0.3478[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]AMS13;AMS20[/C][C]0.4828[/C][C]0.4575[/C][C]0.3911[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]AMS13;AMS27[/C][C]0.4427[/C][C]0.4272[/C][C]0.37[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]AMS20;AMS27[/C][C]0.5539[/C][C]0.5215[/C][C]0.4496[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=272542&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=272542&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
AMS6;AMS130.5420.5350.4607
p-value(0)(0)(0)
AMS6;AMS200.42320.36990.3113
p-value(0)(0)(0)
AMS6;AMS270.45250.41390.3478
p-value(0)(0)(0)
AMS13;AMS200.48280.45750.3911
p-value(0)(0)(0)
AMS13;AMS270.44270.42720.37
p-value(0)(0)(0)
AMS20;AMS270.55390.52150.4496
p-value(0)(0)(0)






Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.01111
0.02111
0.03111
0.04111
0.05111
0.06111
0.07111
0.08111
0.09111
0.1111

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Correlation Tests \tabularnewline
Number of significant by total number of Correlations \tabularnewline
Type I error & Pearson r & Spearman rho & Kendall tau \tabularnewline
0.01 & 1 & 1 & 1 \tabularnewline
0.02 & 1 & 1 & 1 \tabularnewline
0.03 & 1 & 1 & 1 \tabularnewline
0.04 & 1 & 1 & 1 \tabularnewline
0.05 & 1 & 1 & 1 \tabularnewline
0.06 & 1 & 1 & 1 \tabularnewline
0.07 & 1 & 1 & 1 \tabularnewline
0.08 & 1 & 1 & 1 \tabularnewline
0.09 & 1 & 1 & 1 \tabularnewline
0.1 & 1 & 1 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=272542&T=3

[TABLE]
[ROW][C]Meta Analysis of Correlation Tests[/C][/ROW]
[ROW][C]Number of significant by total number of Correlations[/C][/ROW]
[ROW][C]Type I error[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]0.01[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.02[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.03[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.04[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.05[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.06[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.07[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.08[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.09[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.1[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=272542&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=272542&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.01111
0.02111
0.03111
0.04111
0.05111
0.06111
0.07111
0.08111
0.09111
0.1111


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = pearson ;
R code (references can be found in the software module):
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')