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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 computationThu, 09 Oct 2014 23:10:56 +0100
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/Oct/09/t1412892681141hvmgi9ovwr5s.htm/, Retrieved Sat, 11 May 2024 11:12:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=240224, Retrieved Sat, 11 May 2024 11:12:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact271

Tree of Dependent Computations

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 11:23:25] [b98453cac15ba1066b407e146608df68]
- RMP     [Survey Scores] [] [2014-10-09 22:10:56] [63a9f0ea7bb98050796b649e85481845] [Current]
-  M        [Survey Scores] [] [2014-10-10 11:37:31] [6656361aa4da5489a6a45e803df0211c]
-  M        [Survey Scores] [Workshop 3 task 1] [2014-10-11 13:58:51] [261f60062b6e70d0e3f72a6ad4f04654]
-    D      [Survey Scores] [WS3 vraag 1.1] [2014-10-13 09:00:30] [916495ee62ec20121b1928542ac52007]
-    D      [Survey Scores] [E2] [2014-10-14 09:23:01] [2568c9326b0361ae14a2b722dbd6de4e]
-    D      [Survey Scores] [] [2014-10-14 09:38:43] [dacad244957cb51472792888970d4390]
-    D      [Survey Scores] [Blog2] [2014-10-14 09:45:49] [388e7fc45813588c973a58470d39020f]
-           [Survey Scores] [] [2014-10-14 11:38:16] [02fb6cbf799bcf1e525e4e01c2f27ada]
-           [Survey Scores] [] [2014-10-14 11:42:17] [02fb6cbf799bcf1e525e4e01c2f27ada]
-           [Survey Scores] [] [2014-10-14 11:46:17] [02fb6cbf799bcf1e525e4e01c2f27ada]
-           [Survey Scores] [] [2014-10-14 11:47:49] [02fb6cbf799bcf1e525e4e01c2f27ada]
-           [Survey Scores] [Kendall tau rank ...] [2014-10-14 12:53:15] [3d5212c89039da1a3a24d8e18d23c716]
-           [Survey Scores] [] [2014-10-14 14:16:19] [d253a55552bf9917a397def3be261e30]
-             [Survey Scores] [x] [2014-12-23 08:35:32] [1601e79f56036968990446024a6397e5]
-    D      [Survey Scores] [] [2014-10-14 14:42:45] [d253a55552bf9917a397def3be261e30]
-    D      [Survey Scores] [Kendall tau rank ...] [2014-10-14 16:14:38] [3d5212c89039da1a3a24d8e18d23c716]
-             [Survey Scores] [WSH 3 task 1 d] [2014-10-16 18:45:49] [4e6b221caf797a012ce5465db674848b]
-           [Survey Scores] [I2] [2014-10-15 10:41:44] [508ad00fbaced7ad8e80ddb3167ea0fd]
-  M        [Survey Scores] [WS3 reeks 2] [2014-10-15 10:46:36] [2c7dedbadf9652d0ab85aa087468ddf4]
-  M        [Survey Scores] [WS3 reeks 2.2] [2014-10-15 10:48:21] [2c7dedbadf9652d0ab85aa087468ddf4]
-           [Survey Scores] [I2] [2014-10-15 10:48:58] [56d77bf8347cfd1e104fa9098ce46dbd]
-  M        [Survey Scores] [WS3 Question 1] [2014-10-15 11:10:20] [f13ab2b9cdb9c17a0cf473fdf5cac3ab]
-           [Survey Scores] [Tabel 3] [2014-10-15 11:56:20] [36781f05c04c55e165b348994b753b95]
-           [Survey Scores] [Tabel 4] [2014-10-15 12:05:42] [36781f05c04c55e165b348994b753b95]
-  M        [Survey Scores] [Q1] [2014-10-15 12:16:23] [bcf5edf18529a33bd1494456d2c6cb9a]
-  MP       [Survey Scores] [] [2014-10-15 12:18:57] [bcf5edf18529a33bd1494456d2c6cb9a]
-    D      [Survey Scores] [WS3 Task 1 E2] [2014-10-15 12:29:27] [fa1b8827d7de91b8b87087311d3d9fa1]
-    D        [Survey Scores] [WS3 Task 1 E3] [2014-10-15 12:33:56] [fa1b8827d7de91b8b87087311d3d9fa1]
-  M        [Survey Scores] [CP3] [2014-10-15 12:45:05] [ae96d02647dd9ad9c105f1fa6642e295]
-  M        [Survey Scores] [I2] [2014-10-15 12:44:59] [63554e339c9381d8e23ab848f4176daf]
- RM          [Survey Scores] [] [2014-11-30 11:48:48] [f12bfb29749f0c3f544bf278d0782c85]
- R  D          [Survey Scores] [Intrinsieke motiv...] [2014-11-30 14:11:44] [f12bfb29749f0c3f544bf278d0782c85]
- R  D            [Survey Scores] [Extrinsieke motiv...] [2014-11-30 15:11:36] [f12bfb29749f0c3f544bf278d0782c85]
- R  D            [Survey Scores] [Extrinsieke motiv...] [2014-11-30 15:37:01] [f12bfb29749f0c3f544bf278d0782c85]
- R  D            [Survey Scores] [Extrinsieke motiv...] [2014-11-30 15:44:25] [f12bfb29749f0c3f544bf278d0782c85]
- R  D          [Survey Scores] [Intrinsieke motiv...] [2014-11-30 14:40:36] [f12bfb29749f0c3f544bf278d0782c85]
- R  D          [Survey Scores] [Intrinsieke motiv...] [2014-11-30 14:55:20] [f12bfb29749f0c3f544bf278d0782c85]
-  M        [Survey Scores] [Comp 3] [2014-10-15 12:45:41] [ae96d02647dd9ad9c105f1fa6642e295]
-    D      [Survey Scores] [Blog2] [2014-10-15 13:55:36] [a21a52637ee232286cdd7eb4387e60d4]
-           [Survey Scores] [] [2014-10-15 14:09:15] [2b9d0c54c8c845c625e475ed5f1f3af1]
-           [Survey Scores] [Wh 3 - task 1 (3)] [2014-10-15 14:35:03] [0b1d9b19f19fbaaccd0103ec6a2ff37c]
-           [Survey Scores] [WS3 - Q1.1] [2014-10-15 14:38:48] [4d39cf209776852399955073f9d0ee7a]
-           [Survey Scores] [WS 3 task 1 (b)] [2014-10-15 14:44:20] [0b1d9b19f19fbaaccd0103ec6a2ff37c]
-    D      [Survey Scores] [WS3 question 1] [2014-10-15 15:53:21] [a6b2572b29932aa41ecec373f1b28823]
-  M        [Survey Scores] [] [2014-10-15 16:55:48] [69bf0eb8b9b38defaaf4848d8c317571]
-           [Survey Scores] [WS3] [2014-10-15 17:23:28] [1a6d42b46b3d01bc960fcfb45e99fecd]
-           [Survey Scores] [ws3 task 1,1] [2014-10-15 17:39:35] [99723d3e379f668157309b7b2091b15d]
-           [Survey Scores] [WS3 Task 1: surve...] [2014-10-16 08:38:36] [1764622206627ac897c737076a0cb4c8]
-           [Survey Scores] [task 1 i2] [2014-10-16 14:47:45] [673773038936aef3a5778d7e6bda5c1e]

[Truncated]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 0 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=240224&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=240224&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=240224&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 time0 seconds
R Server'Gertrude Mary Cox' @ cox.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)
10.54137490.4783370.38
20.67149410.5792260.56
30.7163490.54103320.53
40.62145440.5393250.58

\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 & 0.54 & 137 & 49 & 0.47 & 83 & 37 & 0.38 \tabularnewline
2 & 0.67 & 149 & 41 & 0.57 & 92 & 26 & 0.56 \tabularnewline
3 & 0.7 & 163 & 49 & 0.54 & 103 & 32 & 0.53 \tabularnewline
4 & 0.62 & 145 & 44 & 0.53 & 93 & 25 & 0.58 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=240224&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]0.54[/C][C]137[/C][C]49[/C][C]0.47[/C][C]83[/C][C]37[/C][C]0.38[/C][/ROW]
[ROW][C]2[/C][C]0.67[/C][C]149[/C][C]41[/C][C]0.57[/C][C]92[/C][C]26[/C][C]0.56[/C][/ROW]
[ROW][C]3[/C][C]0.7[/C][C]163[/C][C]49[/C][C]0.54[/C][C]103[/C][C]32[/C][C]0.53[/C][/ROW]
[ROW][C]4[/C][C]0.62[/C][C]145[/C][C]44[/C][C]0.53[/C][C]93[/C][C]25[/C][C]0.58[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=240224&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=240224&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)
10.54137490.4783370.38
20.67149410.5792260.56
30.7163490.54103320.53
40.62145440.5393250.58






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.878 (0.122)0.755 (0.245)
(Ps-Ns)/(Ps+Ns)0.878 (0.122)1 (0)0.879 (0.121)
(Pc-Nc)/(Pc+Nc)0.755 (0.245)0.879 (0.121)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) & 0.878 (0.122) & 0.755 (0.245) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.878 (0.122) & 1 (0) & 0.879 (0.121) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.755 (0.245) & 0.879 (0.121) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=240224&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]0.878 (0.122)[/C][C]0.755 (0.245)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.878 (0.122)[/C][C]1 (0)[/C][C]0.879 (0.121)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.755 (0.245)[/C][C]0.879 (0.121)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=240224&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=240224&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)0.878 (0.122)0.755 (0.245)
(Ps-Ns)/(Ps+Ns)0.878 (0.122)1 (0)0.879 (0.121)
(Pc-Nc)/(Pc+Nc)0.755 (0.245)0.879 (0.121)1 (0)






Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.083)0.667 (0.333)0 (1)
(Ps-Ns)/(Ps+Ns)0.667 (0.333)1 (0.083)0.333 (0.75)
(Pc-Nc)/(Pc+Nc)0 (1)0.333 (0.75)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) & 0.667 (0.333) & 0 (1) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.667 (0.333) & 1 (0.083) & 0.333 (0.75) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0 (1) & 0.333 (0.75) & 1 (0.083) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=240224&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]0.667 (0.333)[/C][C]0 (1)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.667 (0.333)[/C][C]1 (0.083)[/C][C]0.333 (0.75)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0 (1)[/C][C]0.333 (0.75)[/C][C]1 (0.083)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=240224&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=240224&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)0.667 (0.333)0 (1)
(Ps-Ns)/(Ps+Ns)0.667 (0.333)1 (0.083)0.333 (0.75)
(Pc-Nc)/(Pc+Nc)0 (1)0.333 (0.75)1 (0.083)


Figures (Output of Computation)

Input Parameters & R Code

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')