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Author

*The author of this computation has been verified*

R Software Module

rwasp_surveyscores.wasp

Title produced by software

Survey Scores

Date of computation

Wed, 06 Dec 2017 19:09:36 +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/2017/Dec/06/t15125838208bdmdnc4xjfvo36.htm/, Retrieved Mon, 13 May 2024 23:56:54 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308633, Retrieved Mon, 13 May 2024 23:56:54 +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] [Survey scores: Sy...] [2017-12-06 18:09:36] [dd1b1eac6490c5f5f771b5814b2d0001] [Current]

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2	3	2	3	3	3	4	4	1
4	4	4	3	4	5	5	5	5
4	4	4	4	5	5	5	5	4
5	5	4	4	2	3	4	3	4
4	4	4	4	5	2	5	5	5
4	4	4	5	3	4	5	5	5
4	4	5	4	4	4	5	5	4
4	4	4	4	4	4	5	5	4
3	3	3	3	4	3	4	4	4
2	3	5	3	4	5	5	3	4
4	3	4	4	3	3	3	4	4
4	4	4	4	4	4	4	5	4
4	3	4	4	4	3	5	5	4
4	4	4	4	4	4	5	5	4
3	3	4	3	2	3	4	3	4
3	4	3	3	2	5	4	4	5
4	4	4	4	4	3	5	4	3
4	4	4	4	4	4	3	3	4
5	5	5	5	5	5	5	5	5
2	2	4	4	2	5	3	4	4
3	3	4	4	3	4	4	4	4
3	3	3	4	3	2	4	4	4
4	3	4	4	5	5	5	5	5
4	4	2	5	3	4	4	3	5
4	3	4	4	3	1	4	3	5
2	2	3	3	3	3	4	3	4
3	4	5	4	4	4	3	3	3
5	5	5	5	4	4	4	5	5
4	3	3	4	4	4	4	5	5
3	3	3	4	4	4	4	4	4
4	4	4	5	5	5	5	5	5
3	3	4	4	4	2	5	5	3
1	1	4	1	5	2	1	3	3
3	5	5	5	5	5	5	5	5
2	2	4	4	4	5	5	5	3
3	3	4	3	3	3	5	4	4
4	4	3	3	4	4	4	4	4
2	2	3	3	3	3	4	4	4
3	3	3	3	4	3	3	4	4
3	3	3	3	3	3	3	3	3
4	4	3	2	3	2	4	4	3
4	3	4	4	5	5	5	5	5
2	2	3	2	4	4	3	5	4
4	4	4	5	5	5	5	4	5
3	3	5	4	4	4	4	3	3
4	4	5	4	5	5	5	5	5
3	4	4	5	4	4	5	5	5
4	4	3	3	3	4	5	5	4
2	2	4	3	4	4	5	5	4
4	4	4	3	4	4	3	3	4
5	5	5	4	5	5	5	5	5
3	3	4	4	4	4	4	4	4
3	3	4	4	4	3	4	2	3
4	4	4	3	2	2	5	3	3
4	3	4	4	3	4	5	4	4
4	4	4	5	4	3	5	5	5
4	4	4	3	4	4	4	3	4
4	4	3	4	5	5	4	5	5
3	2	4	3	2	2	3	4	2
4	4	4	4	4	4	5	5	5
3	3	4	4	4	3	3	5	4
3	3	4	4	4	4	4	4	4
4	4	4	4	4	4	4	4	4
3	3	4	3	2	4	5	5	5
3	3	3	4	2	1	5	5	5
3	3	4	4	4	4	4	5	4
3	4	3	4	4	4	4	4	4
4	4	4	4	4	4	4	4	4
4	4	5	5	2	5	5	5	5
4	3	5	3	2	2	4	4	4
2	2	2	4	4	4	5	5	5
3	3	3	4	3	2	3	3	4
4	4	5	4	5	5	5	5	5
3	3	4	5	5	4	5	5	4
4	3	4	4	4	4	4	4	4
3	2	4	4	4	3	4	5	5
2	3	3	3	3	3	4	4	3
4	4	4	4	3	3	5	4	4
2	3	4	1	3	3	3	3	3
4	4	5	4	4	4	4	5	5
2	3	2	3	1	2	3	4	5
3	3	4	3	2	4	4	4	5
3	3	4	3	3	5	5	5	4
3	3	5	5	5	5	5	5	5
4	4	4	3	2	4	5	4	4
2	2	4	3	4	4	5	5	4
4	3	3	4	3	4	4	4	3
3	3	4	4	4	4	4	4	4
3	2	2	3	4	2	4	3	2
4	4	4	4	4	4	4	5	5
3	3	4	4	4	4	5	5	5
4	3	5	4	4	5	5	4	4
3	3	4	5	4	4	4	5	4
5	5	4	4	4	4	4	4	5
2	2	2	3	5	4	3	5	5
4	4	5	5	5	4	5	4	4
1	3	4	4	5	4	5	4	4
2	2	3	5	2	4	5	5	5
3	4	3	4	3	4	4	4	3
2	2	4	4	4	4	4	4	5
2	2	4	5	4	3	4	4	4
2	3	3	4	3	3	4	3	3
4	4	3	5	1	4	5	3	3
4	4	4	4	4	4	4	3	3
4	4	4	5	4	4	4	4	3
4	4	4	4	4	4	5	4	5
3	3	4	4	4	1	4	4	4
2	2	4	5	5	4	4	5	5
3	3	3	3	3	3	3	3	3
3	4	4	3	2	4	4	3	4
3	3	3	2	3	3	4	4	3
2	3	4	4	2	4	5	4	2
2	2	3	3	3	3	4	4	5
2	2	3	3	3	3	4	4	5
3	3	3	3	4	4	5	3	3
4	3	4	4	5	1	4	5	5
5	5	5	4	4	5	5	4	5
3	3	2	2	4	2	5	3	4
4	4	4	4	4	4	4	5	5
3	3	4	4	5	4	3	4	4
2	2	4	3	4	2	4	4	3
4	4	4	3	2	3	4	3	3
3	1	2	3	3	3	3	4	4
3	2	3	2	3	3	3	4	4
3	2	3	3	4	4	4	4	4
3	3	4	4	4	4	4	4	5
3	3	3	4	3	4	4	4	5
3	3	4	4	4	3	4	4	5
2	2	3	2	4	3	4	5	5
3	3	4	3	3	2	4	3	3
2	4	4	3	3	4	4	2	4
2	2	4	4	1	4	4	4	4
3	3	4	3	3	4	4	4	4
4	3	3	4	5	3	2	5	5
3	2	4	4	4	3	4	5	5
4	4	5	5	5	2	5	3	2
4	4	4	4	5	4	5	5	5
3	3	4	4	2	5	4	4	5
1	2	4	2	4	2	4	4	5
3	3	4	4	4	4	4	4	5
3	3	4	3	3	3	4	4	4
4	4	3	4	3	3	5	4	3
3	3	4	4	4	5	5	5	3
1	1	4	4	4	4	4	4	4
3	3	3	3	3	3	3	3	3
3	3	2	2	3	4	3	5	5
1	3	4	3	3	3	3	3	2
4	4	4	4	5	4	5	4	5
4	4	4	4	4	4	4	4	4
4	4	4	3	1	2	5	4	4
4	4	2	4	4	4	3	4	4
4	4	4	3	1	3	4	4	3
3	3	4	4	3	3	3	4	4
2	2	3	5	2	3	5	5	5
4	3	4	3	4	4	4	4	3
4	4	5	5	5	5	5	5	5
3	3	3	4	3	4	5	5	5
4	3	5	4	4	4	4	4	4
5	5	4	4	4	5	5	5	5
2	2	3	3	4	3	4	5	5
2	3	2	3	3	3	4	4	2
3	3	5	3	5	4	5	5	5
1	1	2	4	4	3	3	4	5
3	3	3	2	3	3	3	3	4
3	2	2	3	4	5	3	4	5
3	2	5	3	3	5	3	3	5
4	4	4	4	4	4	4	4	4
4	4	4	3	2	4	5	5	5
1	1	4	3	2	2	4	4	4
3	3	3	4	4	3	4	5	4
3	3	4	3	3	4	4	4	4
4	5	5	4	4	5	5	4	4
4	4	4	4	4	4	4	4	4
4	4	5	3	4	4	4	4	4
4	4	3	3	5	4	4	4	4
2	2	3	4	2	3	5	5	5
3	3	4	4	2	3	4	4	4
4	4	4	4	3	4	5	4	4
4	4	4	4	4	4	4	4	4

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	0 seconds
R Server	Big 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=308633&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=308633&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308633&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	0 seconds
R Server	Big Analytics Cloud Computing Center

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	0.22	84	44	0.31	77	37	0.35
2	0.22	79	40	0.33	70	35	0.33
3	0.75	148	13	0.84	124	13	0.81
4	0.68	134	13	0.82	112	11	0.82
5	0.58	136	32	0.62	108	27	0.6
6	0.63	139	26	0.68	111	22	0.67
7	1.18	215	3	0.97	150	2	0.97
8	1.16	209	2	0.98	146	2	0.97
9	1.12	209	8	0.93	143	7	0.91

\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 & 0.22 & 84 & 44 & 0.31 & 77 & 37 & 0.35 \tabularnewline
2 & 0.22 & 79 & 40 & 0.33 & 70 & 35 & 0.33 \tabularnewline
3 & 0.75 & 148 & 13 & 0.84 & 124 & 13 & 0.81 \tabularnewline
4 & 0.68 & 134 & 13 & 0.82 & 112 & 11 & 0.82 \tabularnewline
5 & 0.58 & 136 & 32 & 0.62 & 108 & 27 & 0.6 \tabularnewline
6 & 0.63 & 139 & 26 & 0.68 & 111 & 22 & 0.67 \tabularnewline
7 & 1.18 & 215 & 3 & 0.97 & 150 & 2 & 0.97 \tabularnewline
8 & 1.16 & 209 & 2 & 0.98 & 146 & 2 & 0.97 \tabularnewline
9 & 1.12 & 209 & 8 & 0.93 & 143 & 7 & 0.91 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308633&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]0.22[/C][C]84[/C][C]44[/C][C]0.31[/C][C]77[/C][C]37[/C][C]0.35[/C][/ROW]
[ROW][C]2[/C][C]0.22[/C][C]79[/C][C]40[/C][C]0.33[/C][C]70[/C][C]35[/C][C]0.33[/C][/ROW]
[ROW][C]3[/C][C]0.75[/C][C]148[/C][C]13[/C][C]0.84[/C][C]124[/C][C]13[/C][C]0.81[/C][/ROW]
[ROW][C]4[/C][C]0.68[/C][C]134[/C][C]13[/C][C]0.82[/C][C]112[/C][C]11[/C][C]0.82[/C][/ROW]
[ROW][C]5[/C][C]0.58[/C][C]136[/C][C]32[/C][C]0.62[/C][C]108[/C][C]27[/C][C]0.6[/C][/ROW]
[ROW][C]6[/C][C]0.63[/C][C]139[/C][C]26[/C][C]0.68[/C][C]111[/C][C]22[/C][C]0.67[/C][/ROW]
[ROW][C]7[/C][C]1.18[/C][C]215[/C][C]3[/C][C]0.97[/C][C]150[/C][C]2[/C][C]0.97[/C][/ROW]
[ROW][C]8[/C][C]1.16[/C][C]209[/C][C]2[/C][C]0.98[/C][C]146[/C][C]2[/C][C]0.97[/C][/ROW]
[ROW][C]9[/C][C]1.12[/C][C]209[/C][C]8[/C][C]0.93[/C][C]143[/C][C]7[/C][C]0.91[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308633&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308633&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	0.22	84	44	0.31	77	37	0.35
2	0.22	79	40	0.33	70	35	0.33
3	0.75	148	13	0.84	124	13	0.81
4	0.68	134	13	0.82	112	11	0.82
5	0.58	136	32	0.62	108	27	0.6
6	0.63	139	26	0.68	111	22	0.67
7	1.18	215	3	0.97	150	2	0.97
8	1.16	209	2	0.98	146	2	0.97
9	1.12	209	8	0.93	143	7	0.91

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.959 (0)	0.963 (0)
(Ps-Ns)/(Ps+Ns)	0.959 (0)	1 (0)	0.998 (0)
(Pc-Nc)/(Pc+Nc)	0.963 (0)	0.998 (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) & 0.959 (0) & 0.963 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.959 (0) & 1 (0) & 0.998 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.963 (0) & 0.998 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308633&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]0.959 (0)[/C][C]0.963 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.959 (0)[/C][C]1 (0)[/C][C]0.998 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.963 (0)[/C][C]0.998 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308633&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308633&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)	0.959 (0)	0.963 (0)
(Ps-Ns)/(Ps+Ns)	0.959 (0)	1 (0)	0.998 (0)
(Pc-Nc)/(Pc+Nc)	0.963 (0)	0.998 (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)	0.93 (0.001)	0.914 (0.001)
(Ps-Ns)/(Ps+Ns)	0.93 (0.001)	1 (0)	0.873 (0.001)
(Pc-Nc)/(Pc+Nc)	0.914 (0.001)	0.873 (0.001)	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) & 0.93 (0.001) & 0.914 (0.001) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.93 (0.001) & 1 (0) & 0.873 (0.001) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.914 (0.001) & 0.873 (0.001) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308633&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]0.93 (0.001)[/C][C]0.914 (0.001)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.93 (0.001)[/C][C]1 (0)[/C][C]0.873 (0.001)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.914 (0.001)[/C][C]0.873 (0.001)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308633&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308633&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)	0.93 (0.001)	0.914 (0.001)
(Ps-Ns)/(Ps+Ns)	0.93 (0.001)	1 (0)	0.873 (0.001)
(Pc-Nc)/(Pc+Nc)	0.914 (0.001)	0.873 (0.001)	1 (0)

Parameters (Session):

par1 = 10 ; par2 = white ; par3 = TRUE ; par4 = Unknown ;

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code