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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 13:06:37 +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/t1418130416lkl6vazsioozipq.htm/, Retrieved Thu, 31 Oct 2024 23:26:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264558, Retrieved Thu, 31 Oct 2024 23:26:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123
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] [4d39cf209776852399955073f9d0ee7a]
-    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] [d784cae208306d5933987ca1a74122e8] [Current]
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Dataseries X:
1	2	2	1
1	1	1	1
2	2	2	2
1	2	1	1
1	1	1	1
5	5	2	5
1	1	1	1
1	1	1	1
1	4	2	1
1	1	1	1
1	3	2	1
1	1	1	1
1	1	1	1
1	2	1	1
1	4	1	1
1	1	1	1
1	1	1	1
1	3	2	1
2	2	5	2
2	2	2	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
2	1	1	2
2	1	3	2
6	5	6	6
1	1	1	1
2	2	2	2
2	2	1	1
1	1	1	1
1	1	1	1
2	2	2	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
2	4	2	2
1	3	1	1
1	2	1	1
1	1	2	1
1	1	1	1
1	1	1	1
2	1	1	1
1	2	1	1
1	2	1	1
1	1	2	1
1	1	1	1
2	2	1	1
1	1	1	1
1	1	1	1
1	1	1	1
2	3	2	2
5	4	5	4
2	2	1	1
2	1	1	1
1	1	1	1
3	5	1	2
1	1	1	1
3	2	3	2
2	2	1	1
2	2	2	2
2	2	2	2
2	2	1	1
2	3	1	2
1	1	1	1
1	1	1	1
3	2	2	2
3	2	2	2
2	1	1	1
1	1	1	1
1	1	1	1
2	4	5	4
2	5	2	1
2	5	1	1
2	2	2	1
2	5	1	1
2	2	1	1
1	1	1	1
1	2	2	2
1	1	1	1
1	4	1	1
1	1	1	1
4	4	4	3
1	1	1	1
3	2	2	2
1	1	1	1
1	1	1	1
7	7	7	7
1	1	1	1
1	1	1	1
1	1	1	1
1	2	1	1
1	1	1	1
1	1	1	1
3	3	3	3
1	2	1	1
1	1	1	1
1	3	1	1
2	2	1	1
1	2	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	4	1	4
2	2	2	1
1	1	1	1
1	1	1	1
1	1	4	1
1	1	1	1
1	1	1	1
3	3	3	3
1	2	1	1
2	3	1	2
2	2	1	1
5	4	4	4
1	1	1	1
2	1	1	1
1	1	1	1
2	1	1	1
1	1	1	2
2	1	1	2
1	1	1	1
1	1	1	1
1	1	1	1
2	2	1	1
2	2	2	2
2	5	1	2
1	1	1	1
2	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
4	6	4	2
1	1	1	1
2	2	1	2
1	1	1	1
1	1	1	1
4	4	2	4
1	2	1	1
1	2	1	1
1	2	1	1
1	2	1	1
2	3	1	1
6	6	4	3
4	4	4	4
1	1	1	1
1	1	1	1
1	1	1	4
2	3	2	2
1	2	1	1
5	3	3	3
1	1	1	1
4	4	4	4
1	1	4	4
1	2	1	1
1	3	1	1
1	1	1	1
1	1	1	1
1	1	1	1
2	1	1	1
1	1	1	1
1	1	1	1
2	1	1	1
1	1	1	1
1	1	1	1
2	1	1	1
2	2	2	2
4	7	3	1
4	1	1	1
1	2	1	1
1	2	3	2
1	5	1	1
1	2	1	1
1	1	1	1
1	1	1	1
3	3	2	3
1	2	1	1
6	7	4	5
1	1	1	1
1	1	1	1
1	1	1	1
1	2	1	1
1	1	1	1
3	5	4	4
2	1	1	1
1	1	1	1
2	2	1	1
2	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
2	2	1	2
1	1	1	1
2	3	2	1
1	3	2	1
1	1	1	1
3	1	1	1
1	2	1	1
2	4	1	1
2	2	2	2
1	1	1	1
3	2	1	1
1	1	1	1
4	5	1	3
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
3	2	1	1
1	1	1	2
1	1	1	1
1	2	1	1
4	5	2	1
2	2	2	2
1	1	1	1
1	1	1	1
3	1	2	2
2	1	1	1
1	1	1	1
1	1	1	1
1	2	2	2
2	1	1	1
2	4	3	4
1	1	1	1
1	1	1	1
1	1	1	1
3	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
2	1	1	1
2	1	1	2
1	1	1	1
1	1	1	1
1	1	1	1
2	2	1	1
2	4	1	2
1	2	1	1
2	2	1	1
1	4	4	4
1	1	1	1
1	2	2	2
1	2	1	1
1	1	1	1
1	1	1	1
1	1	1	1
2	2	1	1
2	2	1	1
2	2	2	2
2	2	1	1
1	2	1	1
1	4	2	2
1	2	2	1
1	1	1	1
2	3	2	2
1	1	1	1
1	1	1	1
1	1	1	1
2	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	2	1	1
2	1	1	1
2	2	2	2
1	1	1	1
1	1	1	1
1	6	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	2	1	1
3	2	1	2
2	2	1	2
1	1	1	1
1	1	1	1
1	1	1	1
2	1	1	1
2	1	1	1
2	2	1	1
3	4	2	3
1	2	1	1
2	3	2	2
2	5	3	2
1	1	1	1
4	4	4	4
1	1	1	1
1	2	1	1
1	1	1	1
1	1	1	1
1	3	1	1
1	1	1	1
1	1	1	1
2	1	1	1
1	2	1	2
1	1	1	2
2	2	1	1
1	1	1	1
1	1	1	1
4	1	1	1
5	2	1	1
1	2	1	1
1	1	1	2
1	1	1	1
1	1	1	1
4	3	3	2
1	1	1	1
2	2	1	1
2	3	2	2
1	1	1	1
1	2	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
3	2	3	3
1	1	1	1
2	2	1	1
1	1	1	1
2	1	1	1
1	1	1	1
1	1	1	1
1	3	1	1
1	1	1	1
1	1	1	4
2	2	2	3
1	2	1	1
3	3	5	3
1	1	1	1
1	1	1	1
1	1	1	1
1	2	1	1
1	1	1	1
1	1	1	1
2	2	4	1
1	1	1	1
1	1	1	1
2	4	3	1
1	1	1	1
1	1	1	1
2	2	1	1
1	1	1	1
2	3	2	2
1	2	1	1
1	1	1	1
2	1	1	1
4	4	3	3
2	2	4	1
1	1	1	1
1	1	1	1
5	5	2	5
1	1	1	1
2	1	1	1
3	2	2	2
2	3	1	1
1	1	1	1
1	2	1	1
2	2	2	1
3	2	3	2
1	2	1	1
1	1	1	1
2	4	1	1
1	1	1	1
1	1	1	1
2	2	1	1
NA	NA	NA	NA
NA	NA	NA	NA
NA	NA	NA	NA
NA	NA	NA	NA
1	2	1	1
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




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=264558&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=264558&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264558&T=0

As an alternative you can also use a 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)
1-1.4338586-0.8823339-0.87
2-1.2269535-0.7741316-0.77
3-1.6229648-0.9120348-0.89
4-1.6327651-0.9219351-0.9

\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 & -1.43 & 38 & 586 & -0.88 & 23 & 339 & -0.87 \tabularnewline
2 & -1.22 & 69 & 535 & -0.77 & 41 & 316 & -0.77 \tabularnewline
3 & -1.62 & 29 & 648 & -0.91 & 20 & 348 & -0.89 \tabularnewline
4 & -1.63 & 27 & 651 & -0.92 & 19 & 351 & -0.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264558&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]-1.43[/C][C]38[/C][C]586[/C][C]-0.88[/C][C]23[/C][C]339[/C][C]-0.87[/C][/ROW]
[ROW][C]2[/C][C]-1.22[/C][C]69[/C][C]535[/C][C]-0.77[/C][C]41[/C][C]316[/C][C]-0.77[/C][/ROW]
[ROW][C]3[/C][C]-1.62[/C][C]29[/C][C]648[/C][C]-0.91[/C][C]20[/C][C]348[/C][C]-0.89[/C][/ROW]
[ROW][C]4[/C][C]-1.63[/C][C]27[/C][C]651[/C][C]-0.92[/C][C]19[/C][C]351[/C][C]-0.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264558&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264558&T=1

As an alternative you can also use a 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)
1-1.4338586-0.8823339-0.87
2-1.2269535-0.7741316-0.77
3-1.6229648-0.9120348-0.89
4-1.6327651-0.9219351-0.9







Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.967 (0.033)0.955 (0.045)
(Ps-Ns)/(Ps+Ns)0.967 (0.033)1 (0)0.999 (0.001)
(Pc-Nc)/(Pc+Nc)0.955 (0.045)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) & 0.967 (0.033) & 0.955 (0.045) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.967 (0.033) & 1 (0) & 0.999 (0.001) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.955 (0.045) & 0.999 (0.001) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264558&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]0.967 (0.033)[/C][C]0.955 (0.045)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.967 (0.033)[/C][C]1 (0)[/C][C]0.999 (0.001)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.955 (0.045)[/C][C]0.999 (0.001)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264558&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264558&T=2

As an alternative you can also use a 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)0.967 (0.033)0.955 (0.045)
(Ps-Ns)/(Ps+Ns)0.967 (0.033)1 (0)0.999 (0.001)
(Pc-Nc)/(Pc+Nc)0.955 (0.045)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=264558&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=264558&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264558&T=3

As an alternative you can also use a 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)



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')