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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 18:56:55 +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/t1418151430m3z6fzosjdy27k5.htm/, Retrieved Thu, 31 Oct 2024 23:06:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264808, Retrieved Thu, 31 Oct 2024 23:06:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122
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] [I3-to experience ...] [2014-12-09 18:50:58] [eee95947b6243a1febfcd5f41483d733]
-    D        [Survey Scores] [E1] [2014-12-09 18:56:55] [ef562ec391a3ad5a7cbe41e167f467b9] [Current]
-    D          [Survey Scores] [E2] [2014-12-09 18:58:12] [eee95947b6243a1febfcd5f41483d733]
-    D            [Survey Scores] [E3] [2014-12-09 18:59:44] [eee95947b6243a1febfcd5f41483d733]
-   PD              [Survey Scores] [a] [2014-12-15 12:03:24] [eee95947b6243a1febfcd5f41483d733]
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Dataseries X:
6	6	6	6
7	4	7	7
5	6	4	4
5	7	6	7
6	6	7	6
7	7	7	7
5	5	4	5
6	6	5	6
7	6	7	6
6	7	6	7
3	3	4	6
6	7	5	7
6	7	3	4
4	6	4	6
6	6	6	6
7	7	7	6
6	6	5	6
6	6	6	6
6	7	7	6
4	4	4	6
7	7	7	7
3	4	3	4
7	7	6	7
5	6	6	7
6	5	5	6
5	7	5	4
6	6	6	6
7	7	5	7
4	4	5	4
6	6	5	6
6	6	4	5
5	4	6	6
6	7	6	5
5	6	6	5
6	5	6	7
6	7	5	6
6	6	6	6
4	7	7	6
6	6	5	6
6	6	6	6
6	6	4	5
6	6	6	5
4	6	5	5
6	6	5	6
6	6	5	6
6	6	5	6
6	6	5	6
7	7	7	6
6	3	5	5
6	7	6	6
6	7	6	6
6	4	6	5
7	7	5	6
4	6	3	4
6	5	6	6
6	7	7	7
7	6	7	7
6	4	4	5
6	6	6	5
7	7	7	4
3	2	6	5
7	7	5	6
7	6	6	7
6	6	6	6
7	7	6	7
5	4	3	7
5	5	5	5
5	6	5	5
7	7	6	6
5	5	6	5
6	7	5	7
7	7	6	7
7	6	6	7
6	7	6	6
7	7	7	7
6	5	5	6
4	5	6	6
5	7	6	6
7	7	5	7
5	7	6	5
5	2	2	6
5	5	6	6
6	7	5	7
7	5	6	6
6	4	5	6
4	4	6	3
7	7	6	6
5	5	5	5
5	6	6	5
7	6	6	5
6	6	5	6
6	6	5	5
7	7	7	7
6	5	5	5
6	6	6	6
7	7	7	7
4	7	7	7
6	6	6	6
6	6	6	6
4	6	5	6
7	7	6	6
6	5	3	2
7	6	5	4
6	6	7	7
7	6	6	7
5	6	5	5
6	6	6	6
2	5	6	6
6	6	5	6
7	7	6	6
5	6	4	5
7	7	6	5
5	4	2	6
5	6	7	6
6	6	4	6
4	5	5	6
7	7	7	7
5	5	5	5
7	6	6	7
5	6	5	5
6	6	4	5
6	6	7	6
6	7	5	7
6	6	6	5
4	6	6	7
7	7	7	7
4	7	5	5
5	5	6	5
7	7	7	7
6	7	7	5
7	7	7	7
7	7	7	7
7	7	7	4
7	7	5	6
7	6	6	7
7	7	6	7
6	6	6	6
6	5	5	5
6	7	7	6
5	7	5	6
5	6	4	5
7	7	5	7
7	7	6	7
6	7	3	5
7	7	7	6
6	7	4	6
5	5	4	6
7	5	7	4
6	5	5	5
7	7	7	7
5	5	6	7
7	6	7	7
6	5	6	6
5	6	5	6
7	6	7	6
5	6	6	6
7	7	7	7
7	6	6	7
6	6	6	6
4	7	6	6
7	7	7	7
5	6	5	5
7	7	7	7
7	6	6	5
6	6	6	4
6	6	7	6
7	7	7	7
6	6	6	6
6	7	6	6
6	6	6	6
6	6	6	7
7	7	6	7
7	7	7	7
7	5	5	6
7	7	6	7
6	5	5	5
5	6	6	7
6	6	6	7
7	7	6	7
4	4	3	3
7	6	5	6
6	6	5	5
4	7	1	4
7	7	6	6
7	6	6	7
7	6	5	6
5	4	4	7
5	6	6	4
7	7	6	6
5	5	4	4
5	6	5	6
6	5	5	6
5	5	5	4
7	7	6	5
7	7	7	7
3	5	3	5
7	7	7	7
6	5	4	6
5	5	6	6
7	6	5	6
7	7	6	6
7	7	7	7
6	6	5	3
7	7	6	6
7	7	7	7
6	5	6	6
6	6	6	6
6	6	5	5
5	5	5	6
4	6	6	5
7	6	6	7
6	6	5	6
6	5	5	5
7	7	6	7
6	5	6	6
7	7	3	6
5	7	6	6
7	7	7	6
6	7	6	6
4	6	7	6
6	6	6	6
5	6	4	5
4	5	5	5
6	5	5	5
4	5	3	6
6	7	7	7
5	6	7	7
5	5	6	5
6	7	7	7
6	5	6	6
7	7	7	6
6	6	6	7
6	6	6	6
7	5	6	5
5	5	6	6
7	7	4	6
3	6	5	5
6	6	6	7
6	6	6	6
7	7	7	7
6	6	5	6
3	4	6	6
6	5	4	4
7	7	6	7
6	6	6	6
7	7	7	5
5	4	7	5
7	7	4	7
4	5	4	6
6	4	5	5
6	6	7	7
7	7	7	6
6	6	5	6
4	5	4	5
6	7	6	4
6	5	5	5
6	6	5	6
4	6	6	6
5	4	6	6
6	6	6	6
6	7	6	7
6	6	6	6
7	6	3	6
6	5	4	5
5	5	4	6
3	5	4	6
6	3	3	6
7	6	6	6
7	7	7	7
7	6	6	4
5	5	5	5
6	4	5	7
6	7	5	5
4	5	6	5
7	6	5	6
4	5	4	5
5	6	6	6
5	5	6	5
4	5	5	5
2	6	5	6
7	6	6	6
3	4	6	5
4	6	6	6
1	1	2	1
6	7	6	5
7	7	7	7
7	7	7	6
3	6	7	7
6	6	6	6
6	7	6	6
4	5	4	6
7	7	4	6
7	7	7	7
5	5	5	4
7	6	5	5
6	7	4	6
6	7	6	7
6	6	7	6
6	6	6	6
5	6	6	6
6	5	5	6
7	6	6	7
5	6	6	6
6	6	5	5
7	5	3	7
4	3	3	7
5	5	5	7
7	6	6	7
6	6	6	6
7	7	6	7
6	5	5	6
7	6	5	5
6	5	5	6
5	6	5	4
7	7	6	7
4	6	4	6
7	5	6	5
4	4	4	4
6	6	6	7
7	5	1	2
6	7	6	6
6	5	5	6
2	7	5	5
5	6	6	5
6	6	6	6
1	1	1	7
7	5	6	6
6	6	6	5
5	6	6	5
6	6	6	6
6	5	5	7
7	7	7	6
7	7	7	7
5	5	5	6
6	6	6	5
7	6	6	6
5	6	5	7
6	6	5	5
6	6	5	6
5	5	6	6
7	7	6	7
7	7	7	3
7	5	6	6
7	6	5	2
4	5	4	6
6	7	5	5
6	5	4	6
7	6	7	7
7	1	5	6
6	6	6	7
6	6	6	7
7	5	6	6
7	7	5	7
5	5	4	7
5	6	5	6
6	7	6	7
6	6	6	2
5	4	6	6
7	7	7	7
7	7	4	7
7	7	6	7
4	5	5	4
4	6	2	2
6	6	6	7
5	5	6	7
6	6	6	6
5	5	5	4
5	5	4	5
6	6	6	5
6	5	5	7
5	5	5	5
7	6	5	5
5	6	5	6
5	6	5	7
6	6	5	5
5	7	6	3
6	5	5	6
7	7	7	5
7	7	3	7
7	4	6	7
7	6	6	7
6	7	6	7
6	6	5	5
7	7	6	7
6	6	6	6
6	5	6	6
7	6	6	5
2	5	2	2
6	7	6	6
2	5	6	6
6	7	6	6
7	7	7	7
3	3	6	6
5	6	6	6
7	4	6	7
7	6	6	6
6	6	6	6
7	6	3	5
6	4	4	5
7	7	4	7
5	6	6	6
6	7	6	6
7	7	6	6
4	5	5	4
6	5	5	6
5	6	5	6
4	4	5	5
7	6	6	6
6	4	6	5
2	7	4	6
5	7	4	5
6	4	6	6
7	7	6	7
4	7	5	7
6	6	5	4
7	7	6	6
7	7	7	7
7	7	7	7
6	6	4	5
5	6	7	6
7	7	7	7
6	5	5	5
7	7	6	6
7	5	3	5
5	5	5	4
6	6	5	6
7	5	7	7
6	6	2	5
2	5	3	5
7	7	6	7
6	7	7	6
6	7	6	6
6	7	7	6
6	6	6	6
7	6	6	6
7	4	6	6
4	4	6	5
5	5	4	5
7	7	7	7
6	6	6	6




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=264808&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=264808&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264808&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'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)
11.82831300.93383190.91
21.9853180.96401100.95
31.5701390.89370270.86
41.84828200.95402120.94

\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 & 1.82 & 831 & 30 & 0.93 & 383 & 19 & 0.91 \tabularnewline
2 & 1.9 & 853 & 18 & 0.96 & 401 & 10 & 0.95 \tabularnewline
3 & 1.5 & 701 & 39 & 0.89 & 370 & 27 & 0.86 \tabularnewline
4 & 1.84 & 828 & 20 & 0.95 & 402 & 12 & 0.94 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264808&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]1.82[/C][C]831[/C][C]30[/C][C]0.93[/C][C]383[/C][C]19[/C][C]0.91[/C][/ROW]
[ROW][C]2[/C][C]1.9[/C][C]853[/C][C]18[/C][C]0.96[/C][C]401[/C][C]10[/C][C]0.95[/C][/ROW]
[ROW][C]3[/C][C]1.5[/C][C]701[/C][C]39[/C][C]0.89[/C][C]370[/C][C]27[/C][C]0.86[/C][/ROW]
[ROW][C]4[/C][C]1.84[/C][C]828[/C][C]20[/C][C]0.95[/C][C]402[/C][C]12[/C][C]0.94[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264808&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264808&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)
11.82831300.93383190.91
21.9853180.96401100.95
31.5701390.89370270.86
41.84828200.95402120.94







Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.967 (0.033)0.958 (0.042)
(Ps-Ns)/(Ps+Ns)0.967 (0.033)1 (0)0.999 (0.001)
(Pc-Nc)/(Pc+Nc)0.958 (0.042)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) & 0.958 (0.042) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.967 (0.033) & 1 (0) & 0.999 (0.001) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.958 (0.042) & 0.999 (0.001) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264808&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]0.958 (0.042)[/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]0.958 (0.042)[/C][C]0.999 (0.001)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264808&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264808&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)0.958 (0.042)
(Ps-Ns)/(Ps+Ns)0.967 (0.033)1 (0)0.999 (0.001)
(Pc-Nc)/(Pc+Nc)0.958 (0.042)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=264808&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=264808&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264808&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 6 7 ;
Parameters (R input):
par1 = 1 2 3 4 5 6 7 ;
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')