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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 computationThu, 19 Dec 2013 03:57:29 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/19/t1387443479665brcq0wv6a1t2.htm/, Retrieved Fri, 29 Mar 2024 15:07:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232444, Retrieved Fri, 29 Mar 2024 15:07:32 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact268
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Survey Scores] [] [2013-12-19 08:57:29] [9e6a405f514733ea23d87e4507d39d29] [Current]
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Dataseries X:
7 7 7 5 5 7 4 5 6 6 4 5
5 5 5 5 4 4 4 4 4 4 3 4
6 5 4 4 5 4 5 5 6 2 5 5
4 5 5 5 4 4 5 5 4 2 2 3
5 5 5 5 4 4 4 4 2 2 2 2
6 6 6 7 6 6 6 5 5 5 5 4
7 4 7 7 5 4 4 4 1 1 1 1
6 5 5 6 3 2 2 5 6 4 5 5
6 7 7 6 4 6 5 4 3 5 4 4
6 5 5 6 4 3 5 4 4 4 3 3
5 2 4 6 2 6 5 6 3 1 1 5
5 5 6 6 5 5 6 4 2 2 5 4
4 5 4 6 3 4 3 3 4 4 3 3
6 6 6 6 5 5 5 5 3 2 2 1
6 6 7 7 6 7 7 7 5 6 6 6
5 5 6 5 4 4 5 4 3 3 3 2
3 3 4 3 3 1 2 2 3 2 2 2
7 6 6 7 6 6 7 6 6 6 6 6
3 5 6 6 7 7 5 7 1 2 1 1
5 5 6 6 2 4 3 4 1 6 4 4
3 3 4 4 6 5 3 5 1 1 1 2
5 5 5 6 4 4 1 6 5 4 5 5
2 1 2 2 1 1 2 1 2 1 1 2
6 5 6 6 4 4 5 3 3 4 3 3
3 4 5 5 3 2 5 4 3 2 2 4
6 6 6 7 6 6 7 5 5 5 6 1
6 6 6 7 6 6 7 5 5 5 6 1
5 4 5 5 3 3 2 1 1 1 1 2
5 4 5 6 6 5 4 4 2 1 2 4
7 5 5 6 4 5 5 5 3 4 4 4
6 4 6 6 7 6 6 6 5 4 4 4
5 5 6 6 4 5 5 5 3 5 4 5
5 6 5 5 4 4 5 5 5 5 4 6
4 3 4 4 3 4 4 4 3 3 3 3
4 5 6 5 4 1 3 4 2 1 1 3
6 5 5 6 6 5 6 4 4 5 3 4
5 3 5 5 3 3 3 3 3 2 1 1
5 5 5 5 2 4 5 4 3 3 3 5
7 7 7 7 7 7 7 7 6 6 6 6
5 6 5 6 7 7 5 6 6 4 3 2
5 4 5 4 5 5 5 4 3 4 4 4
6 5 7 5 5 5 5 5 3 2 2 3
5 5 5 5 6 7 6 5 4 3 3 4
6 6 7 6 7 7 5 7 4 5 4 5
7 7 6 6 6 7 6 6 2 5 3 2
5 3 3 4 3 2 2 5 2 2 2 3
5 4 4 4 4 3 2 3 3 2 2 2
5 6 6 6 4 2 4 5 2 1 1 4
6 5 5 5 4 4 5 4 5 4 4 5
2 2 4 5 2 4 3 5 5 1 2 2
4 4 4 6 4 4 4 4 6 4 3 4
4 4 6 5 3 4 2 2 3 4 4 3
6 5 5 6 5 5 5 5 3 5 4 4
3 4 4 5 3 4 2 2 2 4 2 2
6 6 6 6 5 5 6 6 5 5 4 5
6 2 5 5 5 5 5 5 2 2 2 4
5 4 5 6 4 5 5 5 4 3 3 4
6 6 6 6 5 5 5 2 4 2 2 2
1 4 6 3 5 5 5 6 1 1 1 1
5 5 6 6 6 5 6 6 6 5 4 4
7 6 5 6 4 4 5 5 2 2 1 4
4 4 5 5 4 5 5 3 3 3 3 3
5 6 5 5 7 7 7 6 4 4 4 4
6 6 5 6 6 6 6 7 3 2 1 5
4 5 4 4 5 5 4 5 4 5 4 5
6 6 5 5 6 5 5 6 3 2 1 5
6 6 6 6 6 6 6 6 6 6 6 6
5 4 6 6 5 5 5 5 4 5 4 4
5 6 5 6 4 5 5 5 5 4 4 5
3 3 5 5 2 3 2 4 3 2 2 2
5 5 5 6 7 5 5 5 4 4 5 6
6 5 6 6 5 5 6 6 3 5 5 5
5 5 6 6 5 4 3 4 3 4 3 2
6 6 6 6 6 5 5 4 6 6 5 6
6 6 6 6 6 6 6 6 6 6 5 5
4 4 4 4 4 4 4 4 2 4 4 4
4 4 4 4 4 4 4 4 2 4 4 4
6 5 5 5 6 6 5 5 6 3 3 4
7 6 6 7 6 4 7 7 5 6 5 7
4 3 3 5 5 5 2 4 1 2 3 1
5 6 7 7 7 6 7 7 2 2 4 2
6 2 5 5 3 3 3 2 5 2 2 3
6 5 6 6 6 5 6 4 3 3 3 3
5 3 6 6 5 5 5 5 3 2 3 4
3 4 5 5 6 5 6 3 4 4 5 4
7 6 6 6 7 7 7 6 6 5 5 5
6 5 6 7 4 6 5 5 4 4 4 4
4 4 4 5 2 4 3 3 2 3 3 3
4 5 6 4 3 2 2 1 4 4 4 2
5 5 5 5 5 6 5 5 4 3 3 3
3 4 4 4 5 3 5 5 2 2 2 3
7 7 7 6 6 6 6 6 4 5 5 5
6 4 6 6 3 3 5 5 3 3 3 4
6 6 6 5 3 5 5 5 6 5 4 4
4 4 4 4 5 5 5 5 4 3 3 3
5 4 5 5 5 5 5 5 4 3 3 3
6 6 6 7 3 5 6 5 3 4 2 4
5 3 5 6 4 4 4 5 3 3 4 4
6 4 4 5 1 4 5 6 3 3 3 3
6 7 7 6 7 6 6 7 4 6 6 6
4 5 6 6 4 2 5 4 2 3 3 3
5 5 5 5 7 7 5 3 2 1 1 1
6 6 6 6 4 4 4 5 3 5 5 5
5 5 6 6 5 6 6 6 3 6 5 5
5 5 5 5 5 6 6 4 4 4 3 3
4 4 5 5 6 4 5 4 4 4 3 4
4 5 5 4 4 5 3 2 2 5 3 2
6 6 5 7 4 4 5 4 5 4 4 6
5 5 7 7 4 4 3 1 5 4 1 5
6 5 6 5 6 6 6 6 4 3 5 5
5 4 7 7 4 4 4 6 4 1 2 1
6 4 6 6 3 5 6 6 3 2 3 2
5 5 5 5 3 3 5 5 4 3 2 3
4 5 4 5 5 5 5 5 4 2 3 3
6 6 6 7 5 6 6 5 5 5 5 5
4 5 4 5 3 3 4 2 4 2 3 3
5 3 3 5 4 5 3 4 5 2 2 3
5 5 5 5 5 4 4 4 3 4 3 4
6 3 5 5 5 6 5 6 2 2 1 1
3 4 5 3 3 3 4 2 1 3 3 3
5 4 5 5 3 4 2 5 5 4 5 4
4 5 5 5 5 6 6 6 5 3 4 6
5 2 5 4 3 4 3 5 3 1 1 2
5 5 3 4 4 5 4 4 4 5 4 5
7 7 7 7 7 7 7 7 4 1 1 3
5 6 6 6 6 5 6 3 5 4 4 4
7 6 6 6 5 6 6 6 5 5 6 6
5 5 4 6 2 2 7 2 3 3 3 2
4 4 4 5 4 5 5 4 4 4 3 4
6 6 6 5 6 6 5 6 6 3 3 5
4 3 4 5 6 3 5 5 4 3 4 4
4 7 6 6 5 6 6 6 5 6 6 5
4 3 2 2 4 2 2 4 4 2 1 2
4 4 5 5 4 4 4 4 4 4 2 3
6 6 5 7 5 5 7 6 5 5 4 6
6 5 6 6 3 3 4 3 4 4 3 3
5 6 5 5 5 5 7 5 3 4 2 5
3 4 4 5 5 5 4 4 3 3 2 4
6 6 6 6 5 6 7 5 6 4 5 5
5 6 6 6 6 5 5 4 5 5 5 5
4 4 5 5 4 2 2 2 2 3 2 1
5 5 5 5 3 5 5 4 4 5 4 4
2 3 2 2 3 5 3 7 3 2 2 2
5 6 6 7 4 4 3 4 3 6 4 5
7 5 6 7 5 6 6 6 5 6 4 7
4 6 5 5 5 5 3 4 3 2 2 3
4 5 6 6 3 4 4 6 3 3 3 4
7 6 7 5 6 4 6 6 4 4 3 4
6 5 5 6 5 5 5 5 5 4 4 5
5 6 5 5 4 5 6 5 5 4 5 4
5 5 5 6 5 4 5 5 5 4 2 1
5 5 6 6 4 6 2 6 5 3 2 2
7 6 7 7 7 6 5 4 3 7 5 5
6 5 7 6 5 7 6 2 4 4 2 2
6 6 6 6 3 7 7 5 4 4 4 4
5 5 5 6 5 5 4 4 3 4 4 5
2 4 6 6 2 4 4 6 4 4 4 6
4 4 4 4 4 4 4 4 4 4 4 4
6 4 6 6 3 3 5 5 3 3 3 4
5 5 6 4 4 4 4 4 2 5 4 6
5 4 4 5 5 4 4 4 4 3 2 4
5 5 5 5 4 4 5 5 4 5 4 4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'George Udny Yule' @ yule.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 & 6 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232444&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232444&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232444&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 time6 seconds
R Server'George Udny Yule' @ yule.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)
12.0834360.9714750.93
21.8430570.9614260.92
32.2837330.9815530.96
42.4439830.9915630.96
51.54262120.91125100.85
61.67285150.9136120.84
71.7293170.89130160.78
81.62282190.87137150.8
90.69149380.5988300.49
100.54147590.4388450.32
110.27112680.2472490.19
120.7163500.5396370.44

\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 & 2.08 & 343 & 6 & 0.97 & 147 & 5 & 0.93 \tabularnewline
2 & 1.84 & 305 & 7 & 0.96 & 142 & 6 & 0.92 \tabularnewline
3 & 2.28 & 373 & 3 & 0.98 & 155 & 3 & 0.96 \tabularnewline
4 & 2.44 & 398 & 3 & 0.99 & 156 & 3 & 0.96 \tabularnewline
5 & 1.54 & 262 & 12 & 0.91 & 125 & 10 & 0.85 \tabularnewline
6 & 1.67 & 285 & 15 & 0.9 & 136 & 12 & 0.84 \tabularnewline
7 & 1.7 & 293 & 17 & 0.89 & 130 & 16 & 0.78 \tabularnewline
8 & 1.62 & 282 & 19 & 0.87 & 137 & 15 & 0.8 \tabularnewline
9 & 0.69 & 149 & 38 & 0.59 & 88 & 30 & 0.49 \tabularnewline
10 & 0.54 & 147 & 59 & 0.43 & 88 & 45 & 0.32 \tabularnewline
11 & 0.27 & 112 & 68 & 0.24 & 72 & 49 & 0.19 \tabularnewline
12 & 0.7 & 163 & 50 & 0.53 & 96 & 37 & 0.44 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232444&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]2.08[/C][C]343[/C][C]6[/C][C]0.97[/C][C]147[/C][C]5[/C][C]0.93[/C][/ROW]
[ROW][C]2[/C][C]1.84[/C][C]305[/C][C]7[/C][C]0.96[/C][C]142[/C][C]6[/C][C]0.92[/C][/ROW]
[ROW][C]3[/C][C]2.28[/C][C]373[/C][C]3[/C][C]0.98[/C][C]155[/C][C]3[/C][C]0.96[/C][/ROW]
[ROW][C]4[/C][C]2.44[/C][C]398[/C][C]3[/C][C]0.99[/C][C]156[/C][C]3[/C][C]0.96[/C][/ROW]
[ROW][C]5[/C][C]1.54[/C][C]262[/C][C]12[/C][C]0.91[/C][C]125[/C][C]10[/C][C]0.85[/C][/ROW]
[ROW][C]6[/C][C]1.67[/C][C]285[/C][C]15[/C][C]0.9[/C][C]136[/C][C]12[/C][C]0.84[/C][/ROW]
[ROW][C]7[/C][C]1.7[/C][C]293[/C][C]17[/C][C]0.89[/C][C]130[/C][C]16[/C][C]0.78[/C][/ROW]
[ROW][C]8[/C][C]1.62[/C][C]282[/C][C]19[/C][C]0.87[/C][C]137[/C][C]15[/C][C]0.8[/C][/ROW]
[ROW][C]9[/C][C]0.69[/C][C]149[/C][C]38[/C][C]0.59[/C][C]88[/C][C]30[/C][C]0.49[/C][/ROW]
[ROW][C]10[/C][C]0.54[/C][C]147[/C][C]59[/C][C]0.43[/C][C]88[/C][C]45[/C][C]0.32[/C][/ROW]
[ROW][C]11[/C][C]0.27[/C][C]112[/C][C]68[/C][C]0.24[/C][C]72[/C][C]49[/C][C]0.19[/C][/ROW]
[ROW][C]12[/C][C]0.7[/C][C]163[/C][C]50[/C][C]0.53[/C][C]96[/C][C]37[/C][C]0.44[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232444&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232444&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)
12.0834360.9714750.93
21.8430570.9614260.92
32.2837330.9815530.96
42.4439830.9915630.96
51.54262120.91125100.85
61.67285150.9136120.84
71.7293170.89130160.78
81.62282190.87137150.8
90.69149380.5988300.49
100.54147590.4388450.32
110.27112680.2472490.19
120.7163500.5396370.44







Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.954 (0)0.969 (0)
(Ps-Ns)/(Ps+Ns)0.954 (0)1 (0)0.995 (0)
(Pc-Nc)/(Pc+Nc)0.969 (0)0.995 (0)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) & 0.954 (0) & 0.969 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.954 (0) & 1 (0) & 0.995 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.969 (0) & 0.995 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232444&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]0.954 (0)[/C][C]0.969 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.954 (0)[/C][C]1 (0)[/C][C]0.995 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.969 (0)[/C][C]0.995 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232444&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232444&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)0.954 (0)0.969 (0)
(Ps-Ns)/(Ps+Ns)0.954 (0)1 (0)0.995 (0)
(Pc-Nc)/(Pc+Nc)0.969 (0)0.995 (0)1 (0)







Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.848 (0)0.809 (0)
(Ps-Ns)/(Ps+Ns)0.848 (0)1 (0)0.962 (0)
(Pc-Nc)/(Pc+Nc)0.809 (0)0.962 (0)1 (0)

\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) & 0.848 (0) & 0.809 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.848 (0) & 1 (0) & 0.962 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.809 (0) & 0.962 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232444&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)[/C][C]0.848 (0)[/C][C]0.809 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.848 (0)[/C][C]1 (0)[/C][C]0.962 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.809 (0)[/C][C]0.962 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232444&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232444&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)0.848 (0)0.809 (0)
(Ps-Ns)/(Ps+Ns)0.848 (0)1 (0)0.962 (0)
(Pc-Nc)/(Pc+Nc)0.809 (0)0.962 (0)1 (0)



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')