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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 computationSat, 13 Dec 2014 16:18:00 +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/13/t1418487542eya5gps6xnm1wvy.htm/, Retrieved Thu, 16 May 2024 18:34:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267200, Retrieved Thu, 16 May 2024 18:34:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Percentiles] [Intrinsic Motivat...] [2010-10-12 12:10:58] [b98453cac15ba1066b407e146608df68]
- RMPD  [Kernel Density Estimation] [] [2011-10-18 22:42:23] [b98453cac15ba1066b407e146608df68]
- RMPD    [Percentiles] [] [2011-10-18 22:46:45] [b98453cac15ba1066b407e146608df68]
- RMPD      [Notched Boxplots] [] [2011-10-18 22:58:56] [b98453cac15ba1066b407e146608df68]
- RM D        [Back to Back Histogram] [] [2011-10-18 23:05:48] [b98453cac15ba1066b407e146608df68]
- RMPD            [Survey Scores] [] [2014-12-13 16:18:00] [f11ff77f11120bba23ccca75f7c5b5e0] [Current]
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Post a new message
Dataseries X:
2 2 1 2
4 5 5 4
5 5 5 5
1 2 3 3
5 4 5 5
3 3 3 3
4 4 4 4
5 4 5 3
3 2 2 2
7 7 7 7
6 6 6 2
5 3 5 3
4 6 6 6
3 5 4 5
3 3 3 3
2 5 5 6
NA NA NA NA
3 3 3 3
4 4 4 4
NA NA NA NA
7 4 4 6
6 3 3 3
5 4 4 4
4 5 4 4
4 3 4 6
5 4 4 5
4 4 3 4
NA NA NA NA
NA NA NA NA
6 5 5 5
4 2 4 2
1 3 1 1
4 4 2 3
3 1 1 1
5 5 4 5
4 1 1 6
4 4 3 3
2 3 5 3
2 4 3 3
NA NA NA NA
4 5 5 5
2 3 2 3
2 3 2 3
2 3 3 3
2 3 3 3
2 4 2 2
NA NA NA NA
4 6 6 6
4 2 2 4
NA NA NA NA
4 5 5 6
NA NA NA NA
NA NA NA NA
NA NA NA NA
4 2 2 3
NA NA NA NA
3 4 4 6
2 4 4 4
NA NA NA NA
4 4 4 4
NA NA NA NA
NA NA NA NA
2 4 3 6
2 5 3 5
5 2 2 1
4 2 2 2
4 4 5 5
NA NA NA NA
6 5 5 6
5 2 5 4
2 2 1 5
NA NA NA NA
5 4 3 4
3 4 4 5
NA NA NA NA
NA NA NA NA
4 3 2 4
2 1 1 1
5 5 5 3
2 3 2 3
NA NA NA NA
3 4 4 5
NA NA NA NA
6 3 3 4
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
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
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
4 3 4 4
1 1 1 1
3 2 2 2
4 4 4 6
NA NA NA NA
NA NA NA NA
4 3 3 2
6 4 3 3
4 5 4 4
4 3 3 4
4 3 3 3
5 5 5 5
4 4 4 4
5 3 3 4
2 3 2 3
4 4 4 4
NA NA NA NA
3 4 4 4
6 2 4 4
5 4 5 5
2 4 1 2
5 4 5 5
2 2 1 2
7 5 5 6
3 3 4 4
4 2 2 2
4 4 4 4
4 2 2 4
NA NA NA NA
3 2 1 1
4 6 5 5
3 2 2 2
3 5 2 4
5 2 2 3
4 2 2 2
3 5 4 7
4 4 4 4
1 2 3 5
5 3 2 5
3 4 4 3
3 3 3 2
2 5 3 4
4 4 3 4
1 2 2 2
NA NA NA NA
NA NA NA NA
7 4 4 7
2 5 2 2
NA NA NA NA
NA NA NA NA
NA NA NA NA
NA NA NA NA
3 2 2 5
5 4 4 4
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
3 3 3 4
3 4 4 4
NA NA NA NA
2 3 2 4
1 2 1 3
NA NA NA NA
5 3 2 3
NA NA NA NA
NA NA NA NA
1 2 2 2
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
NA NA NA NA
5 2 2 2
NA NA NA NA
NA NA NA NA
NA NA NA NA
6 7 6 3
NA NA NA NA
5 4 3 3
NA NA NA NA
5 4 3 3
NA NA NA NA
3 2 2 4
NA NA NA NA
NA NA NA NA
NA NA NA NA
NA NA NA NA
NA NA NA NA
3 3 1 3
5 5 4 4
NA NA NA NA
2 3 4 5
2 4 4 6
NA NA NA NA
4 2 1 1
2 5 4 5
NA NA NA NA
NA NA NA NA
4 4 5 4
NA NA NA NA
4 2 3 5
3 2 2 3
4 4 4 4
NA NA NA NA
4 4 4 4
NA NA NA NA
4 4 4 5
3 3 3 3
5 3 3 6
4 4 2 1
NA NA NA NA
4 3 2 3
2 2 2 2
5 4 3 5
NA NA NA NA
6 4 2 5
4 1 1 1
NA NA NA NA
6 4 4 4
NA NA NA NA
NA NA NA NA
NA NA NA NA
3 3 2 5
NA NA NA NA
NA NA NA NA
5 3 3 3
3 2 6 2
5 5 5 4
3 4 3 5
5 3 3 4
1 2 2 3
NA NA NA NA
NA NA NA NA
2 2 4 3
NA NA NA NA
NA NA NA NA
6 4 3 4
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
NA NA NA NA
NA NA NA NA
NA NA NA NA
NA NA NA NA
NA NA NA NA
3 4 2 3
NA NA NA NA
NA NA NA NA
5 4 4 5
0 4 5 4
1 1 2 2
2 5 1 2
5 2 2 3
2 4 2 2
6 3 2 2
3 4 4 4
2 3 1 2
1 1 1 1
1 1 1 1
2 2 2 3
NA NA NA NA
3 4 3 2
NA NA NA NA
3 1 1 1
4 2 2 3
4 1 1 4
5 4 3 4
3 3 3 3
3 2 4 3
4 1 1 5
3 3 3 5
3 1 2 5
5 5 4 5
4 4 4 4
3 5 4 4
4 1 4 2
2 5 2 3
3 2 2 1
3 2 2 2
4 4 3 3
2 3 3 5
1 1 2 3
6 5 1 5
4 1 2 1
3 2 2 2
2 5 4 4
2 3 3 3
2 7 6 5
3 2 4 4
1 2 2 2
2 2 1 3
NA NA NA NA
2 4 4 5
NA NA NA NA
NA NA NA NA
NA NA NA NA
4 5 5 5
2 1 1 1
2 2 3 4
NA NA NA NA
3 1 2 2
4 6 5 4
3 2 4 5
4 7 7 6
NA NA NA NA
3 1 4 4
NA NA NA NA
2 3 3 2
7 5 5 5
5 4 4 5
NA NA NA NA
NA NA NA NA
NA NA NA NA
2 2 2 4
5 5 5 5
4 4 4 5
NA NA NA NA
4 5 4 4
3 3 2 2
6 3 2 4
3 3 4 4
1 3 2 2
4 4 4 5
NA NA NA NA
6 3 3 4
3 3 3 4
NA NA NA NA
NA NA NA NA
NA NA NA NA
3 4 3 4
2 1 1 2
NA NA NA NA
NA NA NA NA
NA NA NA NA
NA NA NA NA
4 4 5 5
NA NA NA NA
NA NA NA NA
4 5 3 4
NA NA NA NA
7 6 6 5
NA NA NA NA
5 4 3 5
NA NA NA NA
2 4 5 5
3 5 5 5
NA NA NA NA
NA NA NA NA
NA NA NA NA
2 1 1 1
NA NA NA NA
2 2 4 2
NA NA NA NA
4 3 4 6
NA NA NA NA
NA NA NA NA
NA NA NA NA
2 4 4 2
NA NA NA NA
4 6 6 6
5 6 3 5
NA NA NA NA
1 1 2 2
NA NA NA NA
1 3 1 2
NA NA NA NA
NA NA NA NA
NA NA NA NA
NA NA NA NA
4 4 3 4
3 2 2 3
4 5 4 5
4 4 5 6
3 3 4 2
4 5 4 3
3 3 3 3
NA NA NA NA
NA NA NA NA
NA NA NA NA
4 4 4 4
3 3 3 3
NA NA NA NA
5 3 5 2
4 5 4 4
NA NA NA NA
4 3 4 3
NA NA NA NA
1 1 1 1
4 3 2 2
NA NA NA NA
2 1 2 2
NA NA NA NA
NA NA NA NA
3 5 5 5
4 2 3 5
4 3 2 2
NA NA NA NA
NA NA NA NA
NA NA NA NA
5 5 3 5
4 5 4 3
NA NA NA NA
NA NA NA NA
NA NA NA NA
NA NA NA NA
NA NA NA NA
NA NA NA NA
6 2 2 1
4 5 5 5
NA NA NA NA
6 4 5 5
NA NA NA NA
4 5 4 4
4 3 1 2
NA NA NA NA
NA NA NA NA
5 1 1 2
4 3 4 5
2 1 2 3
5 1 4 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
3 3 2 3
NA NA NA NA
2 1 1 2
4 4 4 4
NA NA NA NA
4 4 2 4
4 3 4 5
3 3 2 3
NA NA NA NA
NA NA NA NA
NA NA NA NA
NA NA NA NA
4 5 4 4
4 5 3 4
4 5 4 5
NA NA NA NA
NA NA NA NA
NA NA NA NA
NA NA NA NA
NA NA NA NA
4 3 3 5
4 4 4 3
1 5 4 5
NA NA NA NA
NA NA NA NA
NA NA NA NA
NA NA NA NA
4 2 2 2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267200&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]2 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=267200&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267200&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 time2 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)
1-0.4492212-0.3963124-0.33
2-0.6374246-0.5458141-0.42
3-0.8356281-0.6744153-0.55
4-0.38105209-0.3381123-0.21

\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 & -0.44 & 92 & 212 & -0.39 & 63 & 124 & -0.33 \tabularnewline
2 & -0.63 & 74 & 246 & -0.54 & 58 & 141 & -0.42 \tabularnewline
3 & -0.83 & 56 & 281 & -0.67 & 44 & 153 & -0.55 \tabularnewline
4 & -0.38 & 105 & 209 & -0.33 & 81 & 123 & -0.21 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267200&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]-0.44[/C][C]92[/C][C]212[/C][C]-0.39[/C][C]63[/C][C]124[/C][C]-0.33[/C][/ROW]
[ROW][C]2[/C][C]-0.63[/C][C]74[/C][C]246[/C][C]-0.54[/C][C]58[/C][C]141[/C][C]-0.42[/C][/ROW]
[ROW][C]3[/C][C]-0.83[/C][C]56[/C][C]281[/C][C]-0.67[/C][C]44[/C][C]153[/C][C]-0.55[/C][/ROW]
[ROW][C]4[/C][C]-0.38[/C][C]105[/C][C]209[/C][C]-0.33[/C][C]81[/C][C]123[/C][C]-0.21[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267200&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267200&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)
1-0.4492212-0.3963124-0.33
2-0.6374246-0.5458141-0.42
3-0.8356281-0.6744153-0.55
4-0.38105209-0.3381123-0.21







Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.998 (0.002)0.974 (0.026)
(Ps-Ns)/(Ps+Ns)0.998 (0.002)1 (0)0.982 (0.018)
(Pc-Nc)/(Pc+Nc)0.974 (0.026)0.982 (0.018)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) & 0.998 (0.002) & 0.974 (0.026) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.998 (0.002) & 1 (0) & 0.982 (0.018) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.974 (0.026) & 0.982 (0.018) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267200&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]0.998 (0.002)[/C][C]0.974 (0.026)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.998 (0.002)[/C][C]1 (0)[/C][C]0.982 (0.018)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.974 (0.026)[/C][C]0.982 (0.018)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267200&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267200&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)0.998 (0.002)0.974 (0.026)
(Ps-Ns)/(Ps+Ns)0.998 (0.002)1 (0)0.982 (0.018)
(Pc-Nc)/(Pc+Nc)0.974 (0.026)0.982 (0.018)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=267200&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=267200&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267200&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')