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R Software Module

rwasp_surveyscores.wasp

Title produced by software

Survey Scores

Date of computation

Tue, 22 Oct 2013 07:23:44 -0400

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Oct/22/t1382441254cgpx0s734pvnl46.htm/, Retrieved Sun, 28 Apr 2024 22:44:16 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=218190, Retrieved Sun, 28 Apr 2024 22:44:16 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Survey Scores] [WS3: V1] [2013-10-22 11:23:44] [0af71617a8b1f082fed242286206dd2f] [Current]

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Dataseries X:

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Histogram

Boxplots

7 1 4 5 4 7 5 7 1 1
5 3 5 4 5 5 5 5 1 1
5 4 4 5 4 6 5 5 1 2
5 5 5 6 3 6 6 6 2 2
5 5 5 5 6 6 6 6 2 2
7 7 7 7 5 5 5 7 1 1
7 1 4 7 5 7 5 6 1 1
5 5 6 6 1 6 6 7 4 2
3 2 4 7 4 7 7 7 1 1
6 3 3 6 5 6 6 6 1 1
7 6 5 7 6 7 7 7 1 1
6 4 2 5 7 7 6 7 1 1
5 3 3 3 5 6 6 5 1 1
3 3 3 2 6 6 6 6 1 1
7 6 7 7 5 7 6 7 1 1
5 5 5 5 4 6 6 6 2 1
7 5 5 5 7 7 7 7 1 1
7 5 4 6 7 7 7 7 1 1
7 1 6 7 6 7 7 7 1 1
6 5 6 6 6 7 6 6 2 2
5 3 4 5 2 5 5 4 1 1
7 4 6 7 7 7 7 7 1 1
4 2 3 5 5 5 5 6 1 1
7 3 2 5 4 6 7 7 1 1
7 5 5 6 7 7 6 7 1 1
7 5 5 7 1 6 2 5 1 1
7 5 5 7 1 6 2 5 1 1
3 2 1 2 7 6 7 7 1 1
7 4 5 6 4 6 4 6 1 1
5 6 6 6 5 6 4 6 1 1
7 6 5 7 5 6 5 6 1 1
5 4 6 6 5 5 5 6 1 1
5 6 7 6 4 3 4 1 3 2
4 3 4 4 5 3 7 5 3 1
5 6 5 6 5 5 7 7 1 1
6 3 6 6 4 6 4 5 2 2
7 4 7 7 7 7 7 7 1 1
5 4 2 5 7 7 4 5 1 1
7 7 7 7 7 7 6 7 1 1
7 5 5 6 4 6 6 6 1 1
6 5 5 5 7 7 6 7 1 4
6 4 5 6 7 7 6 6 1 1
7 6 6 7 4 6 6 6 1 1
7 4 5 6 3 6 7 5 1 1
6 4 5 6 2 5 6 6 1 1
6 2 4 6 6 6 6 6 4 4
4 3 2 3 4 6 4 5 1 1
7 6 6 6 5 7 7 7 3 3
5 4 4 4 4 6 6 6 1 1
6 6 6 6 7 7 7 7 2 2
5 3 3 4 4 6 6 5 4 1
3 4 3 3 6 5 7 5 1 1
7 5 7 7 7 7 7 7 1 1
6 2 4 4 1 4 2 3 1 1
6 7 4 7 5 7 6 6 1 1
5 6 5 5 4 5 6 6 1 1
5 5 5 5 5 6 5 5 1 1
7 1 2 4 5 7 6 6 1 1
7 6 6 6 5 7 6 6 1 1
7 6 6 6 5 7 6 7 1 1
6 2 5 7 5 7 6 7 1 1
6 5 6 5 5 6 6 6 1 1
7 5 4 4 6 6 4 5 1 1
7 6 6 7 3 6 3 4 1 1
5 5 4 4 4 4 4 5 5 5
7 4 4 7 6 6 7 6 1 1
6 6 6 6 6 6 6 6 2 1
5 2 4 6 3 7 6 7 1 1
6 6 6 6 5 7 7 6 1 1
5 5 5 5 2 7 7 7 1 1
5 4 5 5 7 7 7 7 1 1
6 2 6 6 7 7 5 7 1 1
6 2 2 5 4 6 6 6 1 1
6 5 6 6 6 5 3 5 3 3
7 6 7 6 6 7 6 7 1 1
6 6 5 5 3 5 5 5 2 2
5 5 5 5 3 5 5 5 2 2
7 5 6 6 6 7 6 6 1 1
7 5 7 7 7 7 6 7 1 1
6 5 5 5 3 2 4 3 1 1
7 5 6 7 1 6 4 4 1 1
6 3 2 2 5 6 5 5 2 1
6 4 5 5 5 6 6 6 1 1
7 3 6 6 5 6 5 6 1 1
6 4 6 7 5 5 5 6 2 2
7 7 7 7 6 6 6 6 1 1
7 5 5 5 6 7 7 7 1 1
5 5 5 5 5 5 5 7 4 3
3 1 1 1 7 7 7 7 2 1
6 4 5 6 6 6 7 7 2 2
6 4 5 5 1 5 2 2 1 1
5 3 4 6 3 6 5 5 1 1
6 5 5 7 5 7 4 6 1 1
6 5 3 6 1 7 7 6 1 1
6 6 6 6 6 6 6 6 2 2
7 5 5 5 4 7 7 7 1 4
6 3 6 6 5 6 5 5 1 1
6 3 4 5 5 5 5 5 1 2
6 4 5 6 6 5 4 6 1 1
7 5 5 6 5 6 7 6 1 1
6 5 6 6 5 6 5 7 1 1
5 3 2 5 4 6 4 4 1 1
5 5 6 5 6 6 6 6 2 2
6 6 6 6 6 6 6 6 1 1
6 6 5 6 4 5 5 5 1 1
6 5 5 5 5 5 5 5 3 2
5 4 6 6 5 5 3 5 2 2
6 4 4 6 2 7 5 6 2 1
4 2 4 1 7 7 6 7 1 1
6 3 6 7 5 6 6 6 1 1
7 6 7 7 5 7 7 7 1 1
7 6 6 6 2 7 7 7 1 1
5 6 3 4 3 4 5 5 1 1
5 5 5 5 5 5 5 6 1 1
7 6 5 6 5 7 6 7 1 1
3 2 2 3 5 7 4 7 1 1
7 6 7 7 6 7 7 7 2 1
5 5 5 6 6 6 5 7 1 1
7 3 5 6 4 5 6 5 1 1
5 5 2 6 6 7 7 7 4 1
3 4 3 5 3 4 7 7 2 2
6 6 6 6 6 6 6 6 3 1
5 5 6 6 4 6 6 5 1 1
4 4 3 3 3 3 4 5 3 2
7 7 7 7 4 7 7 7 1 1
6 2 5 5 6 6 6 7 1 1
7 6 7 6 4 7 5 6 1 1
2 6 4 5 6 6 6 6 1 2
5 4 5 5 5 5 5 6 1 1
6 4 6 6 5 6 5 6 1 1
6 3 4 5 5 6 6 6 1 1
6 6 6 6 3 7 6 6 2 1
2 5 3 5 5 6 4 5 1 1
6 6 3 3 4 7 6 6 1 1
7 6 6 7 5 6 7 7 1 1
4 1 3 3 5 6 6 6 1 2
7 5 7 7 1 7 7 7 2 1
7 4 5 5 4 7 7 7 1 1
6 6 5 6 7 7 6 6 1 1
6 6 5 6 4 7 5 6 2 2
2 5 4 4 6 6 5 7 1 2
7 4 5 6 7 7 5 5 1 2
7 5 7 7 6 7 7 5 1 1
5 4 3 4 5 6 3 6 1 1
5 3 6 6 6 7 6 7 1 1
6 3 4 5 5 6 5 5 1 1
5 6 5 6 5 7 7 7 2 1
6 2 4 4 6 6 4 5 1 2
6 4 4 5 5 5 6 6 1 1
6 4 5 5 3 4 4 5 2 2
5 4 5 5 6 7 6 7 1 1
6 5 6 6 7 7 7 7 2 1
7 3 7 7 4 5 4 5 1 1
7 5 6 7 5 7 6 7 1 1
6 4 5 6 4 6 7 6 1 1
6 4 5 6 5 5 5 6 1 1
6 6 6 5 2 6 6 6 1 1
7 7 6 7 7 7 4 7 4 4
6 5 5 7 5 7 4 6 1 1
5 4 3 6 4 6 6 5 2 2
5 3 4 4 2 5 4 5 1 1
5 1 5 5 4 6 3 5 1 1

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=218190&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=218190&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=218190&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 Output	view raw output of R engine
Computing time	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Summary of survey scores (median of Likert score was subtracted)
Question	mean	Sum ofpositives (Ps)	Sum ofnegatives (Ns)	(Ps-Ns)/(Ps+Ns)	Count ofpositives (Pc)	Count ofnegatives (Nc)	(Pc-Nc)/(Pc+Nc)
1	2.8	456	3	0.99	152	3	0.96
2	1.38	251	27	0.81	119	20	0.71
3	1.86	316	14	0.92	135	12	0.84
4	2.52	415	7	0.97	150	5	0.94
5	1.79	313	23	0.86	134	15	0.8
6	3.08	500	1	1	158	1	0.99
7	2.56	419	4	0.98	153	4	0.95
8	2.96	483	3	0.99	158	2	0.98
9	-1.62	8	270	-0.94	7	148	-0.91
10	-1.7	6	281	-0.96	5	154	-0.94

\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 & 2.8 & 456 & 3 & 0.99 & 152 & 3 & 0.96 \tabularnewline
2 & 1.38 & 251 & 27 & 0.81 & 119 & 20 & 0.71 \tabularnewline
3 & 1.86 & 316 & 14 & 0.92 & 135 & 12 & 0.84 \tabularnewline
4 & 2.52 & 415 & 7 & 0.97 & 150 & 5 & 0.94 \tabularnewline
5 & 1.79 & 313 & 23 & 0.86 & 134 & 15 & 0.8 \tabularnewline
6 & 3.08 & 500 & 1 & 1 & 158 & 1 & 0.99 \tabularnewline
7 & 2.56 & 419 & 4 & 0.98 & 153 & 4 & 0.95 \tabularnewline
8 & 2.96 & 483 & 3 & 0.99 & 158 & 2 & 0.98 \tabularnewline
9 & -1.62 & 8 & 270 & -0.94 & 7 & 148 & -0.91 \tabularnewline
10 & -1.7 & 6 & 281 & -0.96 & 5 & 154 & -0.94 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=218190&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]2.8[/C][C]456[/C][C]3[/C][C]0.99[/C][C]152[/C][C]3[/C][C]0.96[/C][/ROW]
[ROW][C]2[/C][C]1.38[/C][C]251[/C][C]27[/C][C]0.81[/C][C]119[/C][C]20[/C][C]0.71[/C][/ROW]
[ROW][C]3[/C][C]1.86[/C][C]316[/C][C]14[/C][C]0.92[/C][C]135[/C][C]12[/C][C]0.84[/C][/ROW]
[ROW][C]4[/C][C]2.52[/C][C]415[/C][C]7[/C][C]0.97[/C][C]150[/C][C]5[/C][C]0.94[/C][/ROW]
[ROW][C]5[/C][C]1.79[/C][C]313[/C][C]23[/C][C]0.86[/C][C]134[/C][C]15[/C][C]0.8[/C][/ROW]
[ROW][C]6[/C][C]3.08[/C][C]500[/C][C]1[/C][C]1[/C][C]158[/C][C]1[/C][C]0.99[/C][/ROW]
[ROW][C]7[/C][C]2.56[/C][C]419[/C][C]4[/C][C]0.98[/C][C]153[/C][C]4[/C][C]0.95[/C][/ROW]
[ROW][C]8[/C][C]2.96[/C][C]483[/C][C]3[/C][C]0.99[/C][C]158[/C][C]2[/C][C]0.98[/C][/ROW]
[ROW][C]9[/C][C]-1.62[/C][C]8[/C][C]270[/C][C]-0.94[/C][C]7[/C][C]148[/C][C]-0.91[/C][/ROW]
[ROW][C]10[/C][C]-1.7[/C][C]6[/C][C]281[/C][C]-0.96[/C][C]5[/C][C]154[/C][C]-0.94[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=218190&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=218190&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)
Question	mean	Sum ofpositives (Ps)	Sum ofnegatives (Ns)	(Ps-Ns)/(Ps+Ns)	Count ofpositives (Pc)	Count ofnegatives (Nc)	(Pc-Nc)/(Pc+Nc)
1	2.8	456	3	0.99	152	3	0.96
2	1.38	251	27	0.81	119	20	0.71
3	1.86	316	14	0.92	135	12	0.84
4	2.52	415	7	0.97	150	5	0.94
5	1.79	313	23	0.86	134	15	0.8
6	3.08	500	1	1	158	1	0.99
7	2.56	419	4	0.98	153	4	0.95
8	2.96	483	3	0.99	158	2	0.98
9	-1.62	8	270	-0.94	7	148	-0.91
10	-1.7	6	281	-0.96	5	154	-0.94

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.972 (0)	0.98 (0)
(Ps-Ns)/(Ps+Ns)	0.972 (0)	1 (0)	0.999 (0)
(Pc-Nc)/(Pc+Nc)	0.98 (0)	0.999 (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) & 0.972 (0) & 0.98 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.972 (0) & 1 (0) & 0.999 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.98 (0) & 0.999 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=218190&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]0.972 (0)[/C][C]0.98 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.972 (0)[/C][C]1 (0)[/C][C]0.999 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.98 (0)[/C][C]0.999 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=218190&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=218190&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)
mean	1 (0)	0.972 (0)	0.98 (0)
(Ps-Ns)/(Ps+Ns)	0.972 (0)	1 (0)	0.999 (0)
(Pc-Nc)/(Pc+Nc)	0.98 (0)	0.999 (0)	1 (0)

Kendall tau rank correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.989 (0)	1 (0)
(Ps-Ns)/(Ps+Ns)	0.989 (0)	1 (0)	0.989 (0)
(Pc-Nc)/(Pc+Nc)	1 (0)	0.989 (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) & 0.989 (0) & 1 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.989 (0) & 1 (0) & 0.989 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 1 (0) & 0.989 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=218190&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]0.989 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.989 (0)[/C][C]1 (0)[/C][C]0.989 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]1 (0)[/C][C]0.989 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=218190&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=218190&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)
mean	1 (0)	0.989 (0)	1 (0)
(Ps-Ns)/(Ps+Ns)	0.989 (0)	1 (0)	0.989 (0)
(Pc-Nc)/(Pc+Nc)	1 (0)	0.989 (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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code