Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_surveyscores.wasp

Title produced by software

Survey Scores

Date of computation

Mon, 17 Aug 2015 22:00:40 +0100

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/2015/Aug/17/t1439845249lmss69w6crxv3e2.htm/, Retrieved Wed, 15 May 2024 14:47:34 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=280245, Retrieved Wed, 15 May 2024 14:47:34 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

152

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 11:18:40] [b98453cac15ba1066b407e146608df68]
- RMP   [Survey Scores] [] [2014-10-09 22:08:50] [32b17a345b130fdf5cc88718ed94a974]
- R  D      [Survey Scores] [] [2015-08-17 21:00:40] [3e99441ea7f7f69c8fa4628f6be951c3] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280245&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280245&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280245&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	2 seconds
R Server	'George Udny Yule' @ yule.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	-0.24	203	325	-0.23	146	203	-0.16
2	-0.47	160	396	-0.42	121	236	-0.32
3	-0.7	128	478	-0.58	101	272	-0.46
4	-0.25	219	344	-0.22	163	206	-0.12

\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 & -0.24 & 203 & 325 & -0.23 & 146 & 203 & -0.16 \tabularnewline
2 & -0.47 & 160 & 396 & -0.42 & 121 & 236 & -0.32 \tabularnewline
3 & -0.7 & 128 & 478 & -0.58 & 101 & 272 & -0.46 \tabularnewline
4 & -0.25 & 219 & 344 & -0.22 & 163 & 206 & -0.12 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280245&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]-0.24[/C][C]203[/C][C]325[/C][C]-0.23[/C][C]146[/C][C]203[/C][C]-0.16[/C][/ROW]
[ROW][C]2[/C][C]-0.47[/C][C]160[/C][C]396[/C][C]-0.42[/C][C]121[/C][C]236[/C][C]-0.32[/C][/ROW]
[ROW][C]3[/C][C]-0.7[/C][C]128[/C][C]478[/C][C]-0.58[/C][C]101[/C][C]272[/C][C]-0.46[/C][/ROW]
[ROW][C]4[/C][C]-0.25[/C][C]219[/C][C]344[/C][C]-0.22[/C][C]163[/C][C]206[/C][C]-0.12[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280245&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280245&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	-0.24	203	325	-0.23	146	203	-0.16
2	-0.47	160	396	-0.42	121	236	-0.32
3	-0.7	128	478	-0.58	101	272	-0.46
4	-0.25	219	344	-0.22	163	206	-0.12

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.998 (0.002)	0.99 (0.01)
(Ps-Ns)/(Ps+Ns)	0.998 (0.002)	1 (0)	0.997 (0.003)
(Pc-Nc)/(Pc+Nc)	0.99 (0.01)	0.997 (0.003)	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) & 0.99 (0.01) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.998 (0.002) & 1 (0) & 0.997 (0.003) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.99 (0.01) & 0.997 (0.003) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280245&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]0.99 (0.01)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.998 (0.002)[/C][C]1 (0)[/C][C]0.997 (0.003)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.99 (0.01)[/C][C]0.997 (0.003)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280245&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280245&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)	0.998 (0.002)	0.99 (0.01)
(Ps-Ns)/(Ps+Ns)	0.998 (0.002)	1 (0)	0.997 (0.003)
(Pc-Nc)/(Pc+Nc)	0.99 (0.01)	0.997 (0.003)	1 (0)

Kendall tau rank correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0.083)	0.667 (0.333)	0.667 (0.333)
(Ps-Ns)/(Ps+Ns)	0.667 (0.333)	1 (0.083)	1 (0.083)
(Pc-Nc)/(Pc+Nc)	0.667 (0.333)	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) & 0.667 (0.333) & 0.667 (0.333) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.667 (0.333) & 1 (0.083) & 1 (0.083) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.667 (0.333) & 1 (0.083) & 1 (0.083) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280245&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]0.667 (0.333)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.667 (0.333)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.667 (0.333)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280245&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280245&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 (0.083)	0.667 (0.333)	0.667 (0.333)
(Ps-Ns)/(Ps+Ns)	0.667 (0.333)	1 (0.083)	1 (0.083)
(Pc-Nc)/(Pc+Nc)	0.667 (0.333)	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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code