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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 computationFri, 15 Dec 2017 20:51:03 +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/2017/Dec/15/t1513367575n92a70bjnr4pc8u.htm/, Retrieved Wed, 15 May 2024 14:30:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309811, Retrieved Wed, 15 May 2024 14:30:16 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
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Estimated Impact76
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
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Dataseries X:
1	3	2	2	1	3
4	5	4	4	5	5
2	4	4	4	4	4
3	4	4	4	4	4
2	3	5	4	5	5
3	3	4	4	5	5
2	4	3	5	4	5
1	3	4	4	4	5
2	3	2	3	4	5
2	4	3	5	4	5
3	3	3	4	4	4
3	3	3	4	4	3
3	3	4	4	4	4
3	4	4	4	4	5
1	2	4	4	4	4
3	4	4	3	5	3
3	2	4	4	3	5
3	3	4	4	4	5
5	3	4	5	5	5
2	3	4	4	4	3
3	4	4	4	4	5
3	2	4	3	4	4
1	3	3	4	5	5
2	2	4	2	5	3
3	4	3	4	5	4
3	2	3	3	4	4
3	4	4	5	3	4
2	3	3	5	5	5
2	3	3	3	5	5
2	3	3	3	4	3
3	5	5	4	5	1
1	2	2	4	3	5
1	2	3	4	3	5
4	1	2	5	5	3
2	4	4	4	3	5
3	4	4	4	4	4
4	3	3	3	4	4
2	4	3	3	4	4
2	2	3	3	4	4
4	4	3	3	3	4
2	3	4	3	3	5
2	3	2	4	5	4
2	2	2	3	4	3
1	2	4	4	5	5
3	4	4	5	3	4
3	2	2	5	5	4
5	4	5	4	5	5
1	3	4	3	4	5
3	5	5	4	4	5
4	4	4	4	4	3
5	5	4	5	5	4
3	2	2	4	4	4
1	4	4	4	3	4
2	3	4	4	3	5
2	3	4	4	4	2
2	3	4	4	5	4
2	3	4	4	4	3
3	3	4	3	5	5
1	2	2	4	2	5
4	4	4	4	5	5
3	3	3	4	4	5
2	3	3	4	4	4
3	3	3	4	4	4
3	3	3	4	5	5
3	2	3	3	5	4
3	4	4	4	4	4
3	3	4	3	4	4
4	4	4	4	4	4
2	4	4	5	5	4
1	4	5	5	4	4
1	2	3	2	5	4
1	4	3	3	4	3
4	3	4	5	5	4
5	4	4	4	4	4
2	3	4	4	4	3
3	3	4	4	5	5
3	3	3	3	3	4
1	2	3	4	4	5
3	4	4	4	3	3
3	4	4	5	5	5
1	4	3	2	5	5
4	4	4	4	5	4
3	3	3	4	4	3
3	3	3	5	5	5
3	4	4	4	4	5
2	4	5	4	4	5
2	3	4	3	3	4
2	3	4	4	4	3
1	3	2	2	2	4
4	4	4	4	5	3
3	4	4	4	5	4
1	4	4	5	4	5
3	4	4	4	4	4
2	3	3	4	5	4
2	2	2	2	5	4
2	2	3	5	4	5
3	2	3	4	4	5
4	2	3	3	5	4
2	3	3	3	3	4
4	4	4	4	5	4
3	3	1	4	4	5
2	3	3	3	3	4
2	3	2	3	3	4
2	2	2	4	3	4
2	4	4	4	3	5
3	4	4	4	5	5
1	3	3	4	4	4
4	3	4	4	5	5
3	3	3	3	3	3
2	3	3	4	4	4
3	2	3	3	3	3
2	2	4	4	2	5
2	2	2	3	5	4
2	2	2	3	5	4
3	4	4	3	3	5
2	3	3	4	5	5
3	3	4	5	5	5
1	2	2	2	4	3
1	1	1	4	5	5
3	4	4	4	4	3
3	4	4	4	3	4
3	4	3	4	3	4
2	1	2	2	4	4
2	2	2	3	4	4
2	3	3	3	4	4
2	4	4	4	5	4
4	4	4	3	5	5
3	3	3	4	5	5
1	2	2	3	5	5
3	3	2	4	3	3
4	4	2	4	4	4
2	3	4	4	4	4
4	4	4	4	4	4
1	2	2	3	5	4
1	2	4	4	5	4
2	1	3	5	2	4
3	3	4	4	5	5
1	3	2	4	5	4
4	3	3	4	5	5
2	3	4	4	5	5
3	2	2	4	4	4
2	2	3	3	3	4
5	3	2	4	3	3
2	2	3	4	4	4
4	3	3	3	3	4
2	1	1	2	5	3
4	3	2	4	2	3
3	5	4	4	5	3
2	4	4	4	4	4
2	2	4	4	4	4
2	2	3	2	4	4
2	4	4	4	3	4
3	3	3	4	4	4
1	3	4	3	5	5
2	4	4	4	3	5
5	2	2	5	5	5
2	4	4	3	5	5
3	3	4	5	4	5
2	2	4	4	5	5
1	3	3	3	5	5
3	3	3	2	2	3
2	4	3	5	5	5
4	3	3	2	5	4
4	2	3	3	4	4
3	3	3	2	5	5
3	3	5	5	5	3
3	4	4	4	4	4
3	3	3	4	5	4
2	2	4	4	4	4
2	4	4	3	4	4
4	3	4	4	4	4
3	3	3	5	4	5
3	4	4	4	4	4
3	3	4	5	4	4
3	3	3	3	4	5
5	3	3	3	5	4
3	4	4	4	4	5
1	3	4	4	4	5
4	4	3	4	4	4
2	2	4	3	5	4
4	4	3	4	3	4
1	2	2	3	5	4
2	4	1	3	5	3
3	4	4	4	4	5
3	4	4	4	4	5
4	4	4	4	5	4
3	4	4	4	4	5
3	3	3	4	3	4
3	3	4	3	5	4
3	4	4	4	5	5
3	3	3	4	4	3
2	2	3	4	4	5
3	3	3	3	5	5
1	1	3	3	4	3
3	3	3	2	5	3
4	3	3	3	5	3
2	3	3	4	3	3
2	4	4	3	4	3
4	2	4	5	2	4
2	3	4	4	4	3
4	4	4	4	4	4
1	2	3	3	3	4
2	1	2	2	5	5
1	2	3	5	3	5
2	3	4	4	4	4
4	3	4	4	4	5
4	3	4	3	5	5
3	4	3	3	5	5
4	3	3	4	3	5
1	4	2	4	2	4
1	4	2	4	2	4
1	2	2	3	5	3
3	3	4	4	4	5
1	2	3	4	4	4
1	1	2	5	5	5
4	4	4	4	5	5
3	4	4	3	5	4
3	2	2	3	5	5
1	2	4	4	4	5
2	3	3	4	5	4
2	3	3	4	5	4
4	2	2	3	4	4
2	2	2	4	5	4
2	4	3	3	4	4
2	3	3	4	5	5
2	2	4	4	5	5
1	2	3	3	5	5
3	3	4	4	5	5
2	3	4	4	4	4
4	4	5	5	5	5
2	3	3	3	3	4
5	3	2	3	5	4
3	3	3	4	4	4
4	3	3	4	4	5
3	4	4	4	4	4
3	4	4	4	4	4
3	4	4	4	4	4
3	4	4	4	5	5
3	2	3	3	5	5
3	5	5	4	5	5
4	3	3	4	4	4
1	2	1	3	5	4
2	2	3	5	4	4
2	2	2	2	1	2
4	4	4	4	4	4
3	3	1	1	2	3
2	2	2	3	4	2
2	2	2	2	4	2
3	4	4	4	4	5
2	4	3	4	5	5
3	3	3	3	3	3
3	4	3	4	5	3
3	2	2	5	5	4
1	1	1	2	4	3
2	3	3	3	3	3
4	4	4	4	4	4
3	3	3	3	3	3
3	2	3	3	4	4
2	2	2	2	4	2
3	2	2	4	4	4
3	2	3	3	2	3
3	3	3	3	3	3
4	4	4	4	3	4
2	4	4	5	4	3
2	5	5	4	5	5
3	4	4	4	4	4
3	3	2	4	4	5
5	4	4	4	5	4
1	2	5	5	5	5
2	3	3	4	4	4
2	4	5	4	5	5
2	4	3	4	4	4
2	4	5	5	4	5
3	4	5	5	5	5
3	4	5	4	5	4
3	2	3	3	4	3
2	4	4	4	5	4
1	3	3	5	5	4
1	3	3	4	4	4
3	3	4	4	4	4
2	2	2	4	5	5
3	2	3	4	5	5
3	4	4	5	1	4
3	4	4	5	5	5
3	3	3	4	5	4
2	3	4	4	5	3
4	3	3	4	3	3
3	4	4	3	5	3
4	3	4	5	5	5
3	5	3	4	3	3
3	3	4	4	5	4
3	4	4	5	5	4
3	1	3	3	2	4
3	3	3	3	5	5
3	4	4	3	3	3
4	3	3	4	4	5
3	1	3	4	4	3
4	4	4	4	4	4
3	4	5	4	5	5
3	3	3	4	4	3
3	4	4	3	3	3
3	4	4	4	5	4
2	3	3	4	3	5
3	3	3	3	3	3
3	3	4	4	5	4
3	4	3	5	4	4
3	5	4	5	5	5
3	4	4	4	4	3
3	4	4	4	4	4
3	2	3	4	3	3
2	2	2	4	5	3
2	4	3	4	5	4
2	3	3	4	4	5
3	3	3	4	2	3
1	2	4	4	5	3
3	3	4	4	3	3
3	3	4	4	4	4
1	3	3	4	3	3
3	4	3	5	5	5
3	4	4	4	5	5
4	3	3	3	4	4
3	3	3	4	4	4
2	4	4	4	4	4
2	4	3	4	5	4
1	3	2	2	2	3
3	3	3	4	2	3
3	4	4	4	4	4
3	4	4	4	5	3
3	4	4	3	4	4
4	2	3	4	4	4
3	4	3	4	4	3
3	4	3	4	3	3
3	3	4	5	3	3
3	4	3	5	3	3
3	4	3	4	4	4
3	2	3	5	5	5
3	4	4	4	5	4
3	4	4	5	5	5
2	4	4	4	3	4
1	2	1	4	4	4
1	3	2	5	4	4
2	2	3	1	5	4
4	4	4	2	4	3
1	3	2	4	4	3
3	3	3	4	3	3
3	4	4	4	4	3
3	4	4	4	4	4
3	4	4	5	4	4
3	5	4	5	5	5
3	4	5	5	5	5
3	4	5	5	3	3
4	4	4	4	4	4
3	3	3	3	4	4
3	3	3	3	3	3
3	3	4	5	4	5
3	3	4	5	5	5
2	4	4	4	5	5
1	4	3	4	3	4
1	3	2	3	4	3
3	4	3	4	4	4
4	3	3	4	3	4
2	4	3	3	4	3
2	4	3	4	4	3
4	2	4	4	5	4
1	3	4	4	3	3
3	3	3	5	5	3
4	2	3	3	5	4
5	4	3	5	3	3
2	2	5	5	4	5
3	4	5	5	5	5
3	4	4	4	5	3
2	4	4	4	3	4
5	5	4	3	4	5
3	3	3	4	5	4
3	4	3	4	4	5
3	4	4	5	4	4
2	3	3	3	5	3
2	5	4	3	5	4
3	4	4	4	2	4
3	5	5	4	5	4
2	2	2	3	3	3
3	3	3	3	4	3
3	3	3	5	5	5
4	3	4	5	3	4
4	4	5	4	4	5
2	4	4	2	4	3
2	2	3	3	4	3
3	3	4	4	4	4
3	3	3	4	4	4
2	4	3	3	3	3
3	4	4	3	4	4
3	4	4	4	5	3
3	3	4	5	4	3
3	4	4	5	4	5
4	5	5	5	4	3
2	2	3	4	5	2
3	4	3	2	4	3
3	4	4	3	5	4
3	3	3	5	4	3
3	3	3	3	3	3
3	4	3	3	4	3
2	4	3	4	4	3
3	4	4	5	4	3
2	2	3	5	5	5
3	3	3	3	4	4
3	4	4	4	5	4
2	4	2	4	4	3
2	3	5	4	4	5
3	3	3	3	5	4
3	3	5	5	4	5
4	4	3	3	4	4
3	3	2	3	4	4
3	3	4	2	4	4
3	4	5	3	4	5
3	4	3	5	4	3
4	4	4	5	5	4
2	2	4	4	5	5
3	3	3	4	4	4
3	2	4	3	4	4
3	4	4	4	4	4
1	2	2	3	5	5
3	3	3	4	5	4
3	3	4	4	5	3
3	3	3	4	4	4
2	4	4	5	4	4
3	4	4	4	4	3
3	4	4	3	3	4
2	3	3	3	3	3
3	4	4	4	4	3
4	4	3	4	5	4
2	2	3	5	4	5
3	3	2	4	5	5
2	4	3	3	5	4
3	5	4	5	5	4
5	5	5	5	5	4
2	3	2	5	4	5
2	2	2	4	3	4
5	4	3	4	3	4
4	3	3	4	4	4
2	3	4	5	5	5
3	3	3	3	4	4
2	4	4	5	5	4
2	4	4	4	5	4
4	5	4	5	5	5
3	4	4	4	5	4
3	4	4	4	4	4




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309811&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=309811&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309811&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center







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)
1-0.3384231-0.4771178-0.43
20.21991090.29182980.3
30.38242730.54215650.54
40.81391280.87314260.85
51.13524220.92357190.9
61.0447480.9733670.96

\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 & -0.33 & 84 & 231 & -0.47 & 71 & 178 & -0.43 \tabularnewline
2 & 0.2 & 199 & 109 & 0.29 & 182 & 98 & 0.3 \tabularnewline
3 & 0.38 & 242 & 73 & 0.54 & 215 & 65 & 0.54 \tabularnewline
4 & 0.81 & 391 & 28 & 0.87 & 314 & 26 & 0.85 \tabularnewline
5 & 1.13 & 524 & 22 & 0.92 & 357 & 19 & 0.9 \tabularnewline
6 & 1.04 & 474 & 8 & 0.97 & 336 & 7 & 0.96 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309811&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]-0.33[/C][C]84[/C][C]231[/C][C]-0.47[/C][C]71[/C][C]178[/C][C]-0.43[/C][/ROW]
[ROW][C]2[/C][C]0.2[/C][C]199[/C][C]109[/C][C]0.29[/C][C]182[/C][C]98[/C][C]0.3[/C][/ROW]
[ROW][C]3[/C][C]0.38[/C][C]242[/C][C]73[/C][C]0.54[/C][C]215[/C][C]65[/C][C]0.54[/C][/ROW]
[ROW][C]4[/C][C]0.81[/C][C]391[/C][C]28[/C][C]0.87[/C][C]314[/C][C]26[/C][C]0.85[/C][/ROW]
[ROW][C]5[/C][C]1.13[/C][C]524[/C][C]22[/C][C]0.92[/C][C]357[/C][C]19[/C][C]0.9[/C][/ROW]
[ROW][C]6[/C][C]1.04[/C][C]474[/C][C]8[/C][C]0.97[/C][C]336[/C][C]7[/C][C]0.96[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309811&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309811&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)
1-0.3384231-0.4771178-0.43
20.21991090.29182980.3
30.38242730.54215650.54
40.81391280.87314260.85
51.13524220.92357190.9
61.0447480.9733670.96







Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.966 (0.002)0.966 (0.002)
(Ps-Ns)/(Ps+Ns)0.966 (0.002)1 (0)1 (0)
(Pc-Nc)/(Pc+Nc)0.966 (0.002)1 (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) & 0.966 (0.002) & 0.966 (0.002) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.966 (0.002) & 1 (0) & 1 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.966 (0.002) & 1 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309811&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]0.966 (0.002)[/C][C]0.966 (0.002)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.966 (0.002)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.966 (0.002)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309811&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309811&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)0.966 (0.002)0.966 (0.002)
(Ps-Ns)/(Ps+Ns)0.966 (0.002)1 (0)1 (0)
(Pc-Nc)/(Pc+Nc)0.966 (0.002)1 (0)1 (0)







Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.003)0.867 (0.017)0.867 (0.017)
(Ps-Ns)/(Ps+Ns)0.867 (0.017)1 (0.003)1 (0.003)
(Pc-Nc)/(Pc+Nc)0.867 (0.017)1 (0.003)1 (0.003)

\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 (0.003) & 0.867 (0.017) & 0.867 (0.017) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.867 (0.017) & 1 (0.003) & 1 (0.003) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.867 (0.017) & 1 (0.003) & 1 (0.003) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309811&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 (0.003)[/C][C]0.867 (0.017)[/C][C]0.867 (0.017)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.867 (0.017)[/C][C]1 (0.003)[/C][C]1 (0.003)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.867 (0.017)[/C][C]1 (0.003)[/C][C]1 (0.003)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309811&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309811&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 (0.003)0.867 (0.017)0.867 (0.017)
(Ps-Ns)/(Ps+Ns)0.867 (0.017)1 (0.003)1 (0.003)
(Pc-Nc)/(Pc+Nc)0.867 (0.017)1 (0.003)1 (0.003)



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)
}
print(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')