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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 computationSun, 14 Dec 2014 09:45:47 +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/14/t1418550352aecgwf2f6f2wrzy.htm/, Retrieved Thu, 16 May 2024 09:41:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267364, Retrieved Thu, 16 May 2024 09:41:08 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134

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 
1 1 1 1
1 2 5 1
1 1 1 1
1 2 1 1
1 1 1 1
1 1 1 1
2 2 2 3
2 2 2 2
3 5 2 1
1 1 1 1
1 1 1 1
1 2 1 2
1 1 1 1
2 2 2 2
1 1 1 1
1 1 1 1
3 2 3 3
1 1 1 1
1 1 1 1
2 2 1 1
1 1 3 1
1 1 1 1
2 3 2 1
1 2 1 1
1 1 1 1
3 4 1 1
1 1 1 1
2 3 1 1
3 3 2 2
1 1 1 1
1 1 1 1
1 4 1 1
2 6 2 2
1 1 1 1
1 4 1 1
2 1 1 1
2 2 2 2
1 2 1 1
1 1 1 1
3 2 2 2
3 2 1 1
1 1 1 1
1 1 1 1
1 1 1 1
1 1 1 1
1 1 1 1
2 3 1 1
1 1 1 1
1 4 1 1
1 1 1 1
1 1 1 1
1 1 1 1
1 1 1 1
2 2 2 2
1 1 1 1
1 1 1 1
1 1 1 1
1 1 1 1
1 2 2 2
3 3 1 5
1 1 1 1
1 1 1 1
1 1 1 1
1 2 1 1
2 6 2 5
1 2 1 1
2 5 2 1
2 2 3 2
1 5 1 1
1 1 1 1
1 2 1 1
1 1 1 1
2 3 2 2
1 1 1 1
1 4 1 4
1 1 1 1
2 3 1 1
1 1 1 1
1 3 1 1
1 4 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 1
1 1 1 1
2 2 1 1
3 2 3 2
2 2 2 1
1 1 1 1
1 1 1 1
2 2 2 1
1 1 1 1
2 2 2 2
3 4 2 2
3 1 1 1
5 3 3 3
1 1 2 1
1 1 1 1
2 3 2 1
2 2 3 2
1 1 1 1
1 1 1 1
1 2 1 1
1 1 1 1
2 1 1 1
1 1 1 1
1 1 1 1
2 2 2 1
3 5 1 1
1 1 1 1
1 1 2 1
1 1 1 1
1 1 1 1
1 1 1 1
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
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
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 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
1 2 1 1

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=267364&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=267364&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267364&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)
1-1.4640763-0.924440-0.9
2-1.2190690-0.7754407-0.77
3-1.6331838-0.9321454-0.91
4-1.6532850-0.9322458-0.91

\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 & -1.46 & 40 & 763 & -0.9 & 24 & 440 & -0.9 \tabularnewline
2 & -1.21 & 90 & 690 & -0.77 & 54 & 407 & -0.77 \tabularnewline
3 & -1.63 & 31 & 838 & -0.93 & 21 & 454 & -0.91 \tabularnewline
4 & -1.65 & 32 & 850 & -0.93 & 22 & 458 & -0.91 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267364&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]-1.46[/C][C]40[/C][C]763[/C][C]-0.9[/C][C]24[/C][C]440[/C][C]-0.9[/C][/ROW]
[ROW][C]2[/C][C]-1.21[/C][C]90[/C][C]690[/C][C]-0.77[/C][C]54[/C][C]407[/C][C]-0.77[/C][/ROW]
[ROW][C]3[/C][C]-1.63[/C][C]31[/C][C]838[/C][C]-0.93[/C][C]21[/C][C]454[/C][C]-0.91[/C][/ROW]
[ROW][C]4[/C][C]-1.65[/C][C]32[/C][C]850[/C][C]-0.93[/C][C]22[/C][C]458[/C][C]-0.91[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267364&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267364&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)
1-1.4640763-0.924440-0.9
2-1.2190690-0.7754407-0.77
3-1.6331838-0.9321454-0.91
4-1.6532850-0.9322458-0.91






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.97 (0.03)0.935 (0.065)
(Ps-Ns)/(Ps+Ns)0.97 (0.03)1 (0)0.993 (0.007)
(Pc-Nc)/(Pc+Nc)0.935 (0.065)0.993 (0.007)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) & 0.97 (0.03) & 0.935 (0.065) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.97 (0.03) & 1 (0) & 0.993 (0.007) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.935 (0.065) & 0.993 (0.007) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267364&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]0.97 (0.03)[/C][C]0.935 (0.065)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.97 (0.03)[/C][C]1 (0)[/C][C]0.993 (0.007)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.935 (0.065)[/C][C]0.993 (0.007)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267364&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267364&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)0.97 (0.03)0.935 (0.065)
(Ps-Ns)/(Ps+Ns)0.97 (0.03)1 (0)0.993 (0.007)
(Pc-Nc)/(Pc+Nc)0.935 (0.065)0.993 (0.007)1 (0)






Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.083)0.913 (0.071)0.913 (0.071)
(Ps-Ns)/(Ps+Ns)0.913 (0.071)1 (0.056)1 (0.056)
(Pc-Nc)/(Pc+Nc)0.913 (0.071)1 (0.056)1 (0.056)

\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) & 0.913 (0.071) & 0.913 (0.071) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.913 (0.071) & 1 (0.056) & 1 (0.056) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.913 (0.071) & 1 (0.056) & 1 (0.056) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267364&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]0.913 (0.071)[/C][C]0.913 (0.071)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.913 (0.071)[/C][C]1 (0.056)[/C][C]1 (0.056)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.913 (0.071)[/C][C]1 (0.056)[/C][C]1 (0.056)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267364&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267364&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)0.913 (0.071)0.913 (0.071)
(Ps-Ns)/(Ps+Ns)0.913 (0.071)1 (0.056)1 (0.056)
(Pc-Nc)/(Pc+Nc)0.913 (0.071)1 (0.056)1 (0.056)


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')