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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, 16 Dec 2014 12:43:13 +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/16/t14187338097lfsaeavfs8lc6p.htm/, Retrieved Thu, 16 May 2024 10:28:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269426, Retrieved Thu, 16 May 2024 10:28:25 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact61

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5 5 5 6
3 4 4 5
6 6 3 5
5 3 2 7
4 4 4 6
2 2 1 6
5 4 5 6
2 2 3 7
3 4 4 6
3 4 4 6
5 5 5 6
2 2 2 6
3 3 2 7
3 2 3 6
3 3 2 4
4 1 1 5
4 4 3 4
5 6 5 5
2 1 2 5
2 2 2 7
4 3 3 5
4 3 4 6
1 3 3 4
5 5 6 6
2 1 2 6
4 4 4 5
3 5 5 5
4 4 3 6
3 4 4 6
4 3 3 5
5 3 3 5
2 2 2 5
3 6 6 6
2 1 1 6
7 2 2 4
6 5 5 6
4 5 5 6
3 4 3 5
2 3 3 4
4 5 4 7
5 4 5 6
5 5 5 6
1 1 1 6
3 5 5 7
2 2 2 7
4 2 3 6
4 7 2 7
6 2 1 4
6 6 4 5
3 4 4 6
5 4 4 6
5 5 6 6
2 2 1 3
4 5 5 5
5 5 5 5
1 2 3 5
5 4 5 6
3 3 3 5
4 4 4 5
5 4 5 5
3 2 2 5
7 7 7 7
6 6 6 4
5 3 5 6
4 6 6 5
3 5 4 7
3 3 3 6
2 5 5 6
3 3 3 5
4 4 4 6
7 4 4 7
6 3 3 5
5 4 4 6
4 5 4 5
4 3 4 6
5 4 4 7
4 4 3 6
6 5 5 6
4 2 4 6
1 3 1 7
4 4 2 5
3 1 1 7
5 5 4 6
4 1 1 6
4 4 3 7
2 3 5 3
2 4 3 7
4 5 5 5
2 3 2 7
2 3 2 5
2 3 3 5
2 3 3 4
2 4 2 7
4 6 6 6
4 2 2 6
4 5 5 6
4 2 2 5
3 4 4 5
2 4 4 6
4 4 4 6
2 4 3 4
2 5 3 4
5 2 2 7
4 2 2 7
4 4 5 6
6 5 5 6
5 2 5 6
2 2 1 6
5 4 3 6
3 4 4 6
4 3 2 4
2 1 1 7
5 5 5 5
2 3 2 6
3 4 4 7
6 3 3 5
3 4 2 3
6 2 3 6
5 5 6 6
3 2 2 6
5 6 5 2
5 6 4 5
4 5 5 4
2 2 2 6
2 3 3 5
5 5 3 5
3 2 2 6
6 5 3 6
4 2 3 6
4 2 2 5
4 6 6 3
3 6 6 6
7 6 5 7
4 3 3 5
4 4 4 6
5 3 3 6
3 4 3 3
3 3 2 5
2 3 2 6
4 4 4 5
4 1 2 6
5 4 4 5
5 4 4 4
5 4 4 6
5 4 4 7
3 4 3 5
3 4 4 4
3 6 6 7
3 6 5 1
6 4 6 6
3 3 2 3
4 4 4 5
4 4 3 7
2 3 3 3
5 5 5 5
5 5 5 4
3 2 2 6
5 3 4 6
1 2 2 5
6 4 3 6
4 3 2 7
4 2 1 7
3 4 3 5
4 2 1 7
2 3 2 4
2 4 3 7
3 3 3 7
5 6 6 7
3 2 2 4
5 5 4 6
4 5 5 7
5 4 2 6
6 6 5 6
4 3 2 7
5 3 4 6
3 3 3 7
2 2 3 6
4 4 3 7
5 3 2 5
3 1 2 5
5 3 4 5
4 5 4 7
3 2 2 7
3 3 3 3
4 5 4 5
4 4 4 6
6 3 3 4
5 5 5 5
5 4 3 6
3 4 3 6
4 3 1 1
7 7 7 7
4 4 5 6
5 4 4 6
4 5 5 5
2 1 1 7
3 4 5 6
5 4 3 7
5 4 4 5
4 4 4 5
2 5 4 7
4 3 4 5
1 1 1 1
3 2 2 7
4 4 4 5
4 3 3 3
6 4 3 4
4 5 4 5
4 3 3 5
4 3 3 1
5 5 5 6
4 4 4 4
5 3 3 5
2 3 2 5
4 4 4 6
3 4 4 6
6 2 4 4
5 4 5 5
2 4 1 6
5 4 5 7
2 2 1 4
7 5 5 6
3 3 4 5
4 2 2 6
4 4 4 6
4 2 2 5
3 2 1 6
4 6 5 7
3 2 2 7
3 5 2 5
5 2 2 6
4 2 2 4
3 5 4 7
4 4 4 5
1 2 3 5
5 3 2 5
3 4 4 3
3 3 3 6
2 5 3 5
4 4 3 6
1 2 2 4
7 4 4 7
2 5 2 7
3 2 2 4
5 4 4 6
3 3 3 6
3 4 4 6
2 3 2 5
1 2 1 4
5 3 2 7
1 2 2 5
5 2 2 7
6 7 6 1
5 4 3 6
5 4 3 5
3 2 2 6
3 3 1 7
5 5 4 7
2 3 4 6
2 4 4 4
4 2 1 5
2 5 4 6
4 4 5 7
4 2 3 4
3 2 2 7
4 4 4 6
4 4 4 5
4 4 4 6
3 3 3 6
5 3 3 4
4 4 2 6
4 3 2 5
2 2 2 6
5 4 3 4
6 4 2 7
4 1 1 4
6 4 4 7
3 3 2 6
5 3 3 3
3 2 6 2
5 5 5 6
3 4 3 7
5 3 3 6
1 2 2 6
2 2 4 6
6 4 3 7
3 4 2 4
3 2 2 6
6 5 5 7
3 5 5 5
5 5 5 5
5 4 5 6
6 1 5 5
5 6 3 5
4 3 2 6
3 3 2 6
4 1 1 7
3 2 2 7
3 4 4 6
4 2 2 5
3 3 3 5
1 5 2 2
4 4 5 6
4 4 4 6
3 4 3 6
4 4 4 5
6 3 3 7
3 4 5 2
5 4 3 5
5 4 6 6
5 4 5 6
3 3 2 5
3 3 3 5
4 4 3 3
4 5 3 6
4 3 4 7
4 1 2 6
4 3 2 7
4 4 4 7
4 4 3 7
3 3 1 2
4 3 2 6
4 4 4 5
6 6 6 6
6 4 5 6
2 3 2 5
5 4 3 5
6 5 4 7
3 1 1 3
4 5 5 7
4 5 5 6
4 2 1 5
4 3 5 7
3 3 3 5
4 4 5 4
2 5 2 4
5 4 5 6
2 3 4 5
3 4 2 5
4 4 4 6
5 5 4 6
2 4 2 6
5 3 3 7
4 3 3 7
4 5 5 6
6 2 3 7
2 3 3 4
6 6 6 7
5 2 4 5
7 6 6 6
4 6 4 6
5 3 3 6
5 3 3 6
5 2 1 7
3 4 3 6
4 4 4 7
4 5 4 7
5 3 3 7
5 4 5 6
5 5 4 7
5 3 3 5
5 4 2 5
4 4 4 7
6 5 5 7
2 2 1 3
6 5 5 6
2 4 4 5
4 4 2 7
5 5 4 6
5 3 3 6
5 3 2 3
5 5 4 5
5 6 5 5
3 5 5 6
5 4 4 6
0 4 5 4
1 1 2 7
2 5 1 7
5 2 2 5
2 4 2 7
6 3 2 7
3 4 4 6
2 3 1 6
1 1 1 1
1 1 1 7
2 2 2 7
3 4 3 5
3 1 1 6
4 2 2 6
4 1 1 6
5 4 3 6
3 3 3 3
3 2 4 5
4 1 1 6
3 3 3 7
3 1 2 6
5 5 4 5
4 4 4 6
5 5 5 4
3 5 4 6
4 1 4 7
2 5 2 2
3 2 2 7
3 2 2 5
4 4 3 6
2 3 3 6
1 1 2 5
6 5 1 7
4 1 2 6
3 2 2 6
2 5 4 7
2 3 3 5
2 7 6 2
3 2 4 7
1 2 2 6
2 2 1 6
2 4 4 7
4 5 5 6
2 1 1 7
2 2 3 5
3 1 2 3
4 6 5 5
3 2 4 7
4 7 7 7
3 1 4 4
2 3 3 7
7 5 5 7
5 4 4 7
2 2 2 6
5 5 5 7
4 4 4 7
4 5 4 7
3 3 2 6
6 3 2 3
3 3 4 5
1 3 2 4
4 4 4 7
6 3 3 7
3 3 3 6
3 4 3 7
2 1 1 6
4 4 5 6
4 5 3 6
7 6 6 6
5 4 3 6
2 4 5 5
3 5 5 6
2 1 1 6
2 2 4 7
4 3 4 7
2 4 4 5
4 6 6 7
5 6 3 6
1 1 2 5
1 3 1 7
4 4 3 5
3 2 2 5
4 5 4 6
4 4 5 5
3 3 4 6
4 5 4 7
3 3 3 4
4 4 4 4
3 3 3 6
5 3 5 5
4 5 4 6
4 3 4 6
1 1 1 5
4 3 2 5
2 1 2 5
3 5 5 6
4 2 3 5
4 3 2 6
5 5 3 5
4 5 4 6
6 2 2 7
4 5 5 6
6 4 5 5
4 5 4 7
4 3 2 5
4 3 1 6
5 1 1 4
4 3 4 5
2 1 2 7
5 1 4 7
3 3 2 7
2 1 1 3
4 4 4 5
4 4 2 6
4 3 4 7
3 3 2 5
4 5 4 7
4 5 3 6
4 5 4 7
4 3 3 5
4 4 4 5
1 5 4 7

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 Maurice George Kendall' @ kendall.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 Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269426&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 Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269426&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269426&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 Maurice George Kendall' @ kendall.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)
10.754971220.61294980.5
20.534221590.452621200.37
30.33542050.272261590.17
42.591307190.97465130.95

\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 & 0.75 & 497 & 122 & 0.61 & 294 & 98 & 0.5 \tabularnewline
2 & 0.53 & 422 & 159 & 0.45 & 262 & 120 & 0.37 \tabularnewline
3 & 0.3 & 354 & 205 & 0.27 & 226 & 159 & 0.17 \tabularnewline
4 & 2.59 & 1307 & 19 & 0.97 & 465 & 13 & 0.95 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269426&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]0.75[/C][C]497[/C][C]122[/C][C]0.61[/C][C]294[/C][C]98[/C][C]0.5[/C][/ROW]
[ROW][C]2[/C][C]0.53[/C][C]422[/C][C]159[/C][C]0.45[/C][C]262[/C][C]120[/C][C]0.37[/C][/ROW]
[ROW][C]3[/C][C]0.3[/C][C]354[/C][C]205[/C][C]0.27[/C][C]226[/C][C]159[/C][C]0.17[/C][/ROW]
[ROW][C]4[/C][C]2.59[/C][C]1307[/C][C]19[/C][C]0.97[/C][C]465[/C][C]13[/C][C]0.95[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269426&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269426&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)
10.754971220.61294980.5
20.534221590.452621200.37
30.33542050.272261590.17
42.591307190.97465130.95






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.953 (0.047)0.969 (0.031)
(Ps-Ns)/(Ps+Ns)0.953 (0.047)1 (0)0.997 (0.003)
(Pc-Nc)/(Pc+Nc)0.969 (0.031)0.997 (0.003)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) & 0.953 (0.047) & 0.969 (0.031) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.953 (0.047) & 1 (0) & 0.997 (0.003) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.969 (0.031) & 0.997 (0.003) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269426&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]0.953 (0.047)[/C][C]0.969 (0.031)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.953 (0.047)[/C][C]1 (0)[/C][C]0.997 (0.003)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.969 (0.031)[/C][C]0.997 (0.003)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269426&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269426&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)0.953 (0.047)0.969 (0.031)
(Ps-Ns)/(Ps+Ns)0.953 (0.047)1 (0)0.997 (0.003)
(Pc-Nc)/(Pc+Nc)0.969 (0.031)0.997 (0.003)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=269426&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=269426&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269426&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')