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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 computationTue, 09 Dec 2014 12:59:24 +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/09/t1418130012huiorzvmvv6a43r.htm/, Retrieved Thu, 16 May 2024 10:34:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264548, Retrieved Thu, 16 May 2024 10:34:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Survey Scores] [1.1 AMSI : kendal...] [2014-12-09 12:27:23] [4d39cf209776852399955073f9d0ee7a]
- R  D  [Survey Scores] [1.1 AMSI : kendal...] [2014-12-09 12:48:59] [4d39cf209776852399955073f9d0ee7a]
-    D    [Survey Scores] [1.1 AMSI : kendal...] [2014-12-09 12:51:00] [4d39cf209776852399955073f9d0ee7a]
-    D      [Survey Scores] [1.1 AMSE : kendal...] [2014-12-09 12:55:02] [4d39cf209776852399955073f9d0ee7a]
-    D          [Survey Scores] [1.1 AMSE : kendal...] [2014-12-09 12:59:24] [d784cae208306d5933987ca1a74122e8] [Current]
-    D            [Survey Scores] [1.1 AMSE : kendal...] [2014-12-09 13:03:29] [4d39cf209776852399955073f9d0ee7a]
-    D              [Survey Scores] [1.1 AMSA : kendal...] [2014-12-09 13:06:37] [4d39cf209776852399955073f9d0ee7a]
- RMP             [Cronbach Alpha] [Cronbach Alpha E2] [2014-12-18 12:19:17] [765bd0d5d4a0c852014c120c6930661d]
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Dataset

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

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'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264548&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264548&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264548&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'Gwilym Jenkins' @ jenkins.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)
12.661030140.9735590.95
21.53648620.83291480.72
31.77730540.86315390.78
42.571000190.96352130.93

\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 & 2.66 & 1030 & 14 & 0.97 & 355 & 9 & 0.95 \tabularnewline
2 & 1.53 & 648 & 62 & 0.83 & 291 & 48 & 0.72 \tabularnewline
3 & 1.77 & 730 & 54 & 0.86 & 315 & 39 & 0.78 \tabularnewline
4 & 2.57 & 1000 & 19 & 0.96 & 352 & 13 & 0.93 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264548&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]2.66[/C][C]1030[/C][C]14[/C][C]0.97[/C][C]355[/C][C]9[/C][C]0.95[/C][/ROW]
[ROW][C]2[/C][C]1.53[/C][C]648[/C][C]62[/C][C]0.83[/C][C]291[/C][C]48[/C][C]0.72[/C][/ROW]
[ROW][C]3[/C][C]1.77[/C][C]730[/C][C]54[/C][C]0.86[/C][C]315[/C][C]39[/C][C]0.78[/C][/ROW]
[ROW][C]4[/C][C]2.57[/C][C]1000[/C][C]19[/C][C]0.96[/C][C]352[/C][C]13[/C][C]0.93[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264548&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264548&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)
12.661030140.9735590.95
21.53648620.83291480.72
31.77730540.86315390.78
42.571000190.96352130.93






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)1 (0)0.999 (0.001)
(Ps-Ns)/(Ps+Ns)1 (0)1 (0)0.999 (0.001)
(Pc-Nc)/(Pc+Nc)0.999 (0.001)0.999 (0.001)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) & 1 (0) & 0.999 (0.001) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 1 (0) & 1 (0) & 0.999 (0.001) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.999 (0.001) & 0.999 (0.001) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264548&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]1 (0)[/C][C]0.999 (0.001)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]1 (0)[/C][C]1 (0)[/C][C]0.999 (0.001)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.999 (0.001)[/C][C]0.999 (0.001)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264548&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264548&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)1 (0)0.999 (0.001)
(Ps-Ns)/(Ps+Ns)1 (0)1 (0)0.999 (0.001)
(Pc-Nc)/(Pc+Nc)0.999 (0.001)0.999 (0.001)1 (0)






Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.083)1 (0.083)1 (0.083)
(Ps-Ns)/(Ps+Ns)1 (0.083)1 (0.083)1 (0.083)
(Pc-Nc)/(Pc+Nc)1 (0.083)1 (0.083)1 (0.083)

\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 (0.083) & 1 (0.083) & 1 (0.083) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 1 (0.083) & 1 (0.083) & 1 (0.083) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 1 (0.083) & 1 (0.083) & 1 (0.083) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264548&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 (0.083)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264548&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264548&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 (0.083)1 (0.083)1 (0.083)
(Ps-Ns)/(Ps+Ns)1 (0.083)1 (0.083)1 (0.083)
(Pc-Nc)/(Pc+Nc)1 (0.083)1 (0.083)1 (0.083)


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')