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_surveyscores.wasp
Title produced by softwareSurvey Scores
Date of computationThu, 04 Dec 2014 22:43:52 +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/2014/Dec/04/t141773304316r2wx3g067nirw.htm/, Retrieved Thu, 16 May 2024 05:30:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263448, Retrieved Thu, 16 May 2024 05:30:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact60

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]
-   PD      [Survey Scores] [] [2014-12-04 22:43:52] [6993448de96b8662e47595bfdf466bf3] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4	4	3	1	4	1	1	1	1	1
3	2	1	2	2	2	2	1	2	1
3	4	2	2	2	2	2	2	2	2
5	4	3	2	5	3	2	4	3	4
1	3	1	2	2	2	1	2	1	2
2	4	2	2	3	3	3	3	3	3
4	4	2	2	2	2	2	2	4	2
4	4	2	3	4	2	2	2	2	2
2	2	2	2	3	4	2	1	2	2
2	4	4	2	3	2	2	2	2	2
2	5	2	1	1	1	1	1	1	1
4	2	2	2	2	2	1	2	2	1
2	4	2	4	4	2	2	2	2	2
3	4	2	2	4	2	2	2	3	2
2	1	1	1	1	1	2	2	2	1
4	5	2	3	5	2	4	3	2	2
4	4	4	5	5	4	3	4	5	4
4	3	2	2	2	4	1	2	2	1
4	4	2	3	3	2	1	2	3	3
3	2	3	2	2	3	1	2	3	3
2	3	2	2	4	2	3	2	2	1
4	4	2	3	4	2	2	2	3	1
4	4	3	3	4	2	2	2	4	2
3	2	2	2	3	2	3	4	1	2
4	4	3	3	3	3	3	3	3	3
4	4	3	4	4	3	3	3	3	3
3	2	2	2	4	2	2	2	2	2
2	2	4	2	2	2	2	2	2	4
2	4	2	2	3	2	1	2	2	1
4	4	3	1	1	1	1	1	1	1
4	4	2	2	4	4	2	3	4	4
5	2	3	1	2	5	4	3	1	5
4	3	2	2	2	2	2	2	2	2
5	5	5	3	5	5	2	3	2	4
4	2	2	1	1	2	4	2	2	2
2	3	1	2	2	1	2	2	2	2
4	5	2	2	4	1	2	4	2	1
4	4	1	4	2	1	3	2	2	2
4	3	2	2	3	2	2	3	2	2
2	2	2	3	1	1	4	4	1	1
3	2	2	1	3	1	1	1	1	1
4	2	2	2	2	2	2	2	2	2
5	5	5	2	4	3	2	3	2	0
4	2	2	2	2	1	1	1	1	1
3	2	3	2	2	3	3	2	3	3
4	5	2	2	3	2	2	2	2	2
2	2	2	1	2	1	2	2	1	1
4	3	1	2	2	2	2	2	2	2
4	5	5	4	4	3	3	5	4	5
4	3	3	2	2	2	3	4	2	2
2	2	2	1	1	1	1	2	1	1
2	2	4	2	3	3	4	4	2	2
3	1	1	1	1	1	1	1	3	2
4	4	3	1	2	4	1	2	3	3
2	2	4	1	1	1	1	1	1	1
2	4	2	2	2	1	2	4	1	1
4	4	2	2	4	2	2	2	4	2
2	2	2	2	2	1	1	2	2	2
2	3	3	1	1	2	2	2	2	2
4	4	2	2	2	2	1	2	2	0
3	2	2	1	2	1	2	2	1	1
5	3	1	1	2	1	2	1	1	1
4	5	4	3	3	3	4	3	2	1
3	2	2	1	2	1	1	2	1	1
4	4	2	2	3	3	3	2	2	2
3	3	1	1	1	2	1	1	2	2
2	2	2	2	3	3	3	2	2	2
2	4	1	1	1	1	3	3	2	1
5	4	5	2	2	1	2	2	4	1
1	2	1	1	1	1	1	1	1	1
4	4	2	2	2	2	3	2	2	2
4	4	2	1	3	4	2	2	2	2
4	3	2	2	2	2	2	2	2	2
3	3	2	3	2	2	3	4	2	2
5	4	2	1	1	1	1	2	1	1
4	4	2	1	2	2	2	2	3	1
2	3	2	1	4	1	2	2	1	1
4	3	2	2	3	2	2	2	2	2
4	4	2	1	3	1	1	1	4	1
2	3	1	1	1	1	1	1	1	1
2	2	1	1	1	1	1	1	1	1
1	3	1	1	2	1	1	2	1	1
3	2	1	1	2	1	3	2	1	1
5	2	2	2	2	1	2	2	2	2
4	3	4	3	3	2	2	2	2	2
3	1	3	4	2	4	3	3	3	3
4	3	2	2	2	3	2	2	3	2
2	4	2	2	2	1	1	2	2	2
4	4	2	4	4	5	2	3	4	5
4	4	1	1	2	2	1	2	4	1
5	4	1	1	3	1	2	2	1	1
4	2	2	2	2	2	2	2	2	2
4	5	2	3	3	4	3	4	2	4
4	4	2	2	2	1	2	2	2	2
4	3	2	2	2	2	2	1	3	2
2	2	1	2	3	1	1	3	2	2
4	4	2	2	3	3	2	2	4	3
2	4	2	1	2	2	2	2	2	2
2	2	2	1	2	2	2	2	2	2
1	4	3	1	2	2	2	4	2	2
4	4	3	3	3	4	3	2	2	2
5	4	3	2	2	3	3	3	3	3
4	2	2	2	2	3	2	2	2	2
3	4	2	4	2	2	4	4	2	2
2	2	1	1	2	1	1	2	2	1
2	4	4	4	3	3	2	3	4	1
2	3	3	2	2	2	3	2	2	2
4	4	2	2	4	2	3	2	2	2
1	2	1	1	1	1	2	2	1	1
4	3	1	2	2	1	2	2	2	1
2	2	1	1	1	1	2	2	1	2

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'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263448&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263448&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263448&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
10.2569410.2559360.24
20.2162390.2353360.19
3-0.7916104-0.731282-0.74
4-1.0410125-0.85989-0.82
5-0.522583-0.542166-0.52
6-0.9515120-0.781282-0.74
7-0.947111-0.88782-0.84
8-0.761498-0.751382-0.73
9-0.8613109-0.791283-0.75
10-1.1112135-0.84992-0.82

\begin{tabular}{lllllllll}
\hline
Summary of survey scores (median of Likert score was subtracted) \tabularnewline
Question & mean & Sum ofpositives (Ps) & Sum ofnegatives (Ns) & (Ps-Ns)/(Ps+Ns) & Count ofpositives (Pc) & Count ofnegatives (Nc) & (Pc-Nc)/(Pc+Nc) \tabularnewline
1 & 0.25 & 69 & 41 & 0.25 & 59 & 36 & 0.24 \tabularnewline
2 & 0.21 & 62 & 39 & 0.23 & 53 & 36 & 0.19 \tabularnewline
3 & -0.79 & 16 & 104 & -0.73 & 12 & 82 & -0.74 \tabularnewline
4 & -1.04 & 10 & 125 & -0.85 & 9 & 89 & -0.82 \tabularnewline
5 & -0.52 & 25 & 83 & -0.54 & 21 & 66 & -0.52 \tabularnewline
6 & -0.95 & 15 & 120 & -0.78 & 12 & 82 & -0.74 \tabularnewline
7 & -0.94 & 7 & 111 & -0.88 & 7 & 82 & -0.84 \tabularnewline
8 & -0.76 & 14 & 98 & -0.75 & 13 & 82 & -0.73 \tabularnewline
9 & -0.86 & 13 & 109 & -0.79 & 12 & 83 & -0.75 \tabularnewline
10 & -1.11 & 12 & 135 & -0.84 & 9 & 92 & -0.82 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263448&T=1

[TABLE]
[ROW][C]Summary of survey scores (median of Likert score was subtracted)[/C][/ROW]
[ROW][C]Question[/C][C]mean[/C][C]Sum ofpositives (Ps)[/C][C]Sum ofnegatives (Ns)[/C][C](Ps-Ns)/(Ps+Ns)[/C][C]Count ofpositives (Pc)[/C][C]Count ofnegatives (Nc)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]1[/C][C]0.25[/C][C]69[/C][C]41[/C][C]0.25[/C][C]59[/C][C]36[/C][C]0.24[/C][/ROW]
[ROW][C]2[/C][C]0.21[/C][C]62[/C][C]39[/C][C]0.23[/C][C]53[/C][C]36[/C][C]0.19[/C][/ROW]
[ROW][C]3[/C][C]-0.79[/C][C]16[/C][C]104[/C][C]-0.73[/C][C]12[/C][C]82[/C][C]-0.74[/C][/ROW]
[ROW][C]4[/C][C]-1.04[/C][C]10[/C][C]125[/C][C]-0.85[/C][C]9[/C][C]89[/C][C]-0.82[/C][/ROW]
[ROW][C]5[/C][C]-0.52[/C][C]25[/C][C]83[/C][C]-0.54[/C][C]21[/C][C]66[/C][C]-0.52[/C][/ROW]
[ROW][C]6[/C][C]-0.95[/C][C]15[/C][C]120[/C][C]-0.78[/C][C]12[/C][C]82[/C][C]-0.74[/C][/ROW]
[ROW][C]7[/C][C]-0.94[/C][C]7[/C][C]111[/C][C]-0.88[/C][C]7[/C][C]82[/C][C]-0.84[/C][/ROW]
[ROW][C]8[/C][C]-0.76[/C][C]14[/C][C]98[/C][C]-0.75[/C][C]13[/C][C]82[/C][C]-0.73[/C][/ROW]
[ROW][C]9[/C][C]-0.86[/C][C]13[/C][C]109[/C][C]-0.79[/C][C]12[/C][C]83[/C][C]-0.75[/C][/ROW]
[ROW][C]10[/C][C]-1.11[/C][C]12[/C][C]135[/C][C]-0.84[/C][C]9[/C][C]92[/C][C]-0.82[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263448&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263448&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:

Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
10.2569410.2559360.24
20.2162390.2353360.19
3-0.7916104-0.731282-0.74
4-1.0410125-0.85989-0.82
5-0.522583-0.542166-0.52
6-0.9515120-0.781282-0.74
7-0.947111-0.88782-0.84
8-0.761498-0.751382-0.73
9-0.8613109-0.791283-0.75
10-1.1112135-0.84992-0.82






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.986 (0)0.986 (0)
(Ps-Ns)/(Ps+Ns)0.986 (0)1 (0)0.999 (0)
(Pc-Nc)/(Pc+Nc)0.986 (0)0.999 (0)1 (0)

\begin{tabular}{lllllllll}
\hline
Pearson correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0) & 0.986 (0) & 0.986 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.986 (0) & 1 (0) & 0.999 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.986 (0) & 0.999 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263448&T=2

[TABLE]
[ROW][C]Pearson correlations of survey scores (and p-values)[/C][/ROW]
[ROW][C][/C][C]mean[/C][C](Ps-Ns)/(Ps+Ns)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]mean[/C][C]1 (0)[/C][C]0.986 (0)[/C][C]0.986 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.986 (0)[/C][C]1 (0)[/C][C]0.999 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.986 (0)[/C][C]0.999 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263448&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263448&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:

Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.986 (0)0.986 (0)
(Ps-Ns)/(Ps+Ns)0.986 (0)1 (0)0.999 (0)
(Pc-Nc)/(Pc+Nc)0.986 (0)0.999 (0)1 (0)






Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.733 (0.002)0.796 (0.002)
(Ps-Ns)/(Ps+Ns)0.733 (0.002)1 (0)0.932 (0)
(Pc-Nc)/(Pc+Nc)0.796 (0.002)0.932 (0)1 (0)

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0) & 0.733 (0.002) & 0.796 (0.002) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.733 (0.002) & 1 (0) & 0.932 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.796 (0.002) & 0.932 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263448&T=3

[TABLE]
[ROW][C]Kendall tau rank correlations of survey scores (and p-values)[/C][/ROW]
[ROW][C][/C][C]mean[/C][C](Ps-Ns)/(Ps+Ns)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]mean[/C][C]1 (0)[/C][C]0.733 (0.002)[/C][C]0.796 (0.002)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.733 (0.002)[/C][C]1 (0)[/C][C]0.932 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.796 (0.002)[/C][C]0.932 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263448&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263448&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:

Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.733 (0.002)0.796 (0.002)
(Ps-Ns)/(Ps+Ns)0.733 (0.002)1 (0)0.932 (0)
(Pc-Nc)/(Pc+Nc)0.796 (0.002)0.932 (0)1 (0)


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 2 3 4 5 ;
Parameters (R input):
par1 = 1 2 3 4 5 ;
R code (references can be found in the software module):
docor <- function(x,y,method) {
r <- cor.test(x,y,method=method)
paste(round(r$estimate,3),' (',round(r$p.value,3),')',sep='')
}
x <- t(x)
nx <- length(x[,1])
cx <- length(x[1,])
mymedian <- median(as.numeric(strsplit(par1,' ')[[1]]))
myresult <- array(NA, dim = c(cx,7))
rownames(myresult) <- paste('Q',1:cx,sep='')
colnames(myresult) <- c('mean','Sum of
positives (Ps)','Sum of
negatives (Ns)', '(Ps-Ns)/(Ps+Ns)', 'Count of
positives (Pc)', 'Count of
negatives (Nc)', '(Pc-Nc)/(Pc+Nc)')
for (i in 1:cx) {
spos <- 0
sneg <- 0
cpos <- 0
cneg <- 0
for (j in 1:nx) {
if (!is.na(x[j,i])) {
myx <- as.numeric(x[j,i]) - mymedian
if (myx > 0) {
spos = spos + myx
cpos = cpos + 1
}
if (myx < 0) {
sneg = sneg + abs(myx)
cneg = cneg + 1
}
}
}
myresult[i,1] <- round(mean(as.numeric(x[,i]),na.rm=T)-mymedian,2)
myresult[i,2] <- spos
myresult[i,3] <- sneg
myresult[i,4] <- round((spos - sneg) / (spos + sneg),2)
myresult[i,5] <- cpos
myresult[i,6] <- cneg
myresult[i,7] <- round((cpos - cneg) / (cpos + cneg),2)
}
myresult
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of survey scores (median of Likert score was subtracted)',8,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Question',header=TRUE)
for (i in 1:7) {
a<-table.element(a,colnames(myresult)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:cx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
for (j in 1:7) {
a<-table.element(a,myresult[i,j],align='right')
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Kendall tau rank correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')