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Author*The author of this computation has been verified*
R Software ModulePatrick.Wessarwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationSat, 11 Dec 2010 08:13:41 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/11/t1292055309za6v3o8i4pusjdx.htm/, Retrieved Mon, 06 May 2024 11:27:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108007, Retrieved Mon, 06 May 2024 11:27:23 +0000
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Estimated Impact180
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [] [2010-12-05 18:04:16] [b98453cac15ba1066b407e146608df68]
-   PD    [Kendall tau Correlation Matrix] [] [2010-12-11 08:13:41] [6ff6d3268c67efbfcd6d6506b34b66fb] [Current]
-   PD      [Kendall tau Correlation Matrix] [kendall's tau matrix] [2010-12-11 09:52:00] [f730b099f190102bcd41f590a8dae16d]
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Dataseries X:
13	15	2	9	42	9
12	18	1	9	51	9
15	11	1	9	42	9
12	16	1	8	46	8
10	12	2	14	41	14
12	17	2	14	49	14
15	15	1	15	47	15
9	19	1	11	33	11
11	18	1	8	47	8
11	10	2	14	42	14
11	14	1	9	32	9
15	18	1	6	53	6
7	18	2	14	41	14
11	14	2	8	41	8
11	14	1	11	33	11
10	12	1	16	37	16
14	16	2	11	43	11
6	13	2	13	33	13
11	16	1	7	49	7
15	14	2	9	42	9
11	9	1	15	43	15
12	9	2	16	37	16
14	17	1	10	43	10
15	13	2	14	42	14
9	15	2	12	43	12
13	17	1	6	46	6
13	16	2	4	33	4
16	12	1	12	42	12
13	11	1	14	40	14
12	16	2	13	44	13
14	17	1	9	42	9
11	17	2	14	52	14
9	16	1	14	44	14
16	13	2	10	45	10
12	12	1	14	46	14
10	12	2	8	36	8
13	16	1	8	45	8
16	14	1	10	49	10
14	12	2	9	43	9
15	12	1	9	43	9
5	14	1	11	37	11
8	8	2	15	32	15
11	15	1	9	45	9
16	14	2	9	45	9
17	11	1	10	45	10
9	13	2	8	45	8
9	14	1	8	31	8
13	15	1	14	33	14
10	16	1	10	44	10
6	10	2	11	49	11
12	11	2	9	44	9
8	12	2	12	41	12
14	14	2	13	44	13
12	15	1	14	38	14
11	16	1	15	33	15
16	9	1	11	47	11
8	11	2	9	37	9
15	15	1	8	48	8
7	15	2	7	40	7
16	13	2	10	50	10
14	17	1	10	54	10
16	17	1	10	43	10
9	15	1	9	54	9
14	13	1	13	44	13
11	15	2	11	47	11
13	13	2	8	33	8
15	15	1	10	45	10
5	10	2	14	33	14
15	15	1	11	44	11
13	14	1	10	47	10
11	15	2	16	45	16
11	16	2	11	43	11
12	7	1	16	43	16
12	13	1	6	33	6
12	15	1	11	46	11
14	13	1	14	47	14
6	16	1	9	47	9
7	16	2	9	0	9
14	12	1	11	43	11
13	15	2	12	46	12
12	14	2	20	36	20
9	11	2	11	42	11
12	14	1	12	44	12
16	15	1	9	47	9
10	9	2	10	41	10
14	15	1	14	47	14
10	17	1	8	46	8
16	16	1	10	47	10
15	14	1	8	46	8
12	15	2	7	46	7
10	16	1	11	36	11
8	10	1	14	30	14
8	17	2	8	48	8
11	15	2	14	45	14
13	15	1	10	49	10
16	13	1	9	55	9
14	14	2	16	11	16
11	16	1	8	52	8
4	11	2	12	33	12
14	18	1	8	47	8
9	14	1	16	33	16
14	14	1	13	44	13
8	14	1	13	42	13
8	14	1	8	55	8
11	15	1	9	42	9
12	14	1	11	46	11
14	15	1	9	46	9
15	15	2	8	47	8
16	12	1	14	33	14
16	19	1	7	53	7
14	13	2	11	42	11
12	15	1	11	44	11
14	17	2	10	55	10
8	9	2	14	40	14
16	15	2	10	46	10
12	16	1	9	53	9
12	17	1	8	44	8
11	11	1	14	35	14
4	15	1	12	40	12
16	11	1	12	44	12
15	15	1	6	46	6
10	17	1	16	45	16
13	14	1	8	53	8
15	12	2	13	45	13
12	14	1	12	48	12
14	15	2	11	46	11
7	16	1	12	55	12
19	16	1	9	47	9
12	14	1	11	43	11
12	11	2	16	38	16
8	14	2	10	40	10
12	13	1	13	47	13
10	13	1	11	47	11
8	14	2	11	42	11
10	16	2	9	53	9
14	16	2	11	43	11
16	12	1	12	44	12
13	11	1	10	42	10
16	13	1	13	51	13
9	15	1	9	54	9
14	13	2	14	41	14
14	16	2	14	51	14
12	13	1	8	51	8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108007&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108007&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108007&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 time3 seconds
R Server'George Udny Yule' @ 72.249.76.132







Correlations for all pairs of data series (method=pearson)
popularityhapinessgenderdoubsaboutactionsbelongingparentalexpectations
popularity10.078-0.192-0.1290.286-0.129
hapiness0.0781-0.164-0.3530.248-0.353
gender-0.192-0.16410.132-0.2060.132
doubsaboutactions-0.129-0.3530.1321-0.2531
belonging0.2860.248-0.206-0.2531-0.253
parentalexpectations-0.129-0.3530.1321-0.2531

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & popularity & hapiness & gender & doubsaboutactions & belonging & parentalexpectations \tabularnewline
popularity & 1 & 0.078 & -0.192 & -0.129 & 0.286 & -0.129 \tabularnewline
hapiness & 0.078 & 1 & -0.164 & -0.353 & 0.248 & -0.353 \tabularnewline
gender & -0.192 & -0.164 & 1 & 0.132 & -0.206 & 0.132 \tabularnewline
doubsaboutactions & -0.129 & -0.353 & 0.132 & 1 & -0.253 & 1 \tabularnewline
belonging & 0.286 & 0.248 & -0.206 & -0.253 & 1 & -0.253 \tabularnewline
parentalexpectations & -0.129 & -0.353 & 0.132 & 1 & -0.253 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108007&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]popularity[/C][C]hapiness[/C][C]gender[/C][C]doubsaboutactions[/C][C]belonging[/C][C]parentalexpectations[/C][/ROW]
[ROW][C]popularity[/C][C]1[/C][C]0.078[/C][C]-0.192[/C][C]-0.129[/C][C]0.286[/C][C]-0.129[/C][/ROW]
[ROW][C]hapiness[/C][C]0.078[/C][C]1[/C][C]-0.164[/C][C]-0.353[/C][C]0.248[/C][C]-0.353[/C][/ROW]
[ROW][C]gender[/C][C]-0.192[/C][C]-0.164[/C][C]1[/C][C]0.132[/C][C]-0.206[/C][C]0.132[/C][/ROW]
[ROW][C]doubsaboutactions[/C][C]-0.129[/C][C]-0.353[/C][C]0.132[/C][C]1[/C][C]-0.253[/C][C]1[/C][/ROW]
[ROW][C]belonging[/C][C]0.286[/C][C]0.248[/C][C]-0.206[/C][C]-0.253[/C][C]1[/C][C]-0.253[/C][/ROW]
[ROW][C]parentalexpectations[/C][C]-0.129[/C][C]-0.353[/C][C]0.132[/C][C]1[/C][C]-0.253[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108007&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108007&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series (method=pearson)
popularityhapinessgenderdoubsaboutactionsbelongingparentalexpectations
popularity10.078-0.192-0.1290.286-0.129
hapiness0.0781-0.164-0.3530.248-0.353
gender-0.192-0.16410.132-0.2060.132
doubsaboutactions-0.129-0.3530.1321-0.2531
belonging0.2860.248-0.206-0.2531-0.253
parentalexpectations-0.129-0.3530.1321-0.2531







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
popularity;hapiness0.07830.01580.0065
p-value(0.3524)(0.8512)(0.9166)
popularity;gender-0.1917-0.1796-0.1539
p-value(0.0218)(0.0318)(0.0323)
popularity;doubsaboutactions-0.1294-0.1229-0.0894
p-value(0.1234)(0.1435)(0.1494)
popularity;belonging0.2860.30580.2262
p-value(5e-04)(2e-04)(2e-04)
popularity;parentalexpectations-0.1294-0.1229-0.0894
p-value(0.1234)(0.1435)(0.1494)
hapiness;gender-0.1643-0.1534-0.1327
p-value(0.0499)(0.0674)(0.0676)
hapiness;doubsaboutactions-0.353-0.3318-0.257
p-value(0)(1e-04)(0)
hapiness;belonging0.24820.37550.2779
p-value(0.0028)(0)(0)
hapiness;parentalexpectations-0.353-0.3318-0.257
p-value(0)(1e-04)(0)
gender;doubsaboutactions0.13230.12780.1101
p-value(0.1151)(0.1282)(0.1278)
gender;belonging-0.2061-0.2284-0.1925
p-value(0.0136)(0.0061)(0.0065)
gender;parentalexpectations0.13230.12780.1101
p-value(0.1151)(0.1282)(0.1278)
doubsaboutactions;belonging-0.2531-0.3138-0.2368
p-value(0.0023)(1e-04)(1e-04)
doubsaboutactions;parentalexpectations111
p-value(0)(0)(0)
belonging;parentalexpectations-0.2531-0.3138-0.2368
p-value(0.0023)(1e-04)(1e-04)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
popularity;hapiness & 0.0783 & 0.0158 & 0.0065 \tabularnewline
p-value & (0.3524) & (0.8512) & (0.9166) \tabularnewline
popularity;gender & -0.1917 & -0.1796 & -0.1539 \tabularnewline
p-value & (0.0218) & (0.0318) & (0.0323) \tabularnewline
popularity;doubsaboutactions & -0.1294 & -0.1229 & -0.0894 \tabularnewline
p-value & (0.1234) & (0.1435) & (0.1494) \tabularnewline
popularity;belonging & 0.286 & 0.3058 & 0.2262 \tabularnewline
p-value & (5e-04) & (2e-04) & (2e-04) \tabularnewline
popularity;parentalexpectations & -0.1294 & -0.1229 & -0.0894 \tabularnewline
p-value & (0.1234) & (0.1435) & (0.1494) \tabularnewline
hapiness;gender & -0.1643 & -0.1534 & -0.1327 \tabularnewline
p-value & (0.0499) & (0.0674) & (0.0676) \tabularnewline
hapiness;doubsaboutactions & -0.353 & -0.3318 & -0.257 \tabularnewline
p-value & (0) & (1e-04) & (0) \tabularnewline
hapiness;belonging & 0.2482 & 0.3755 & 0.2779 \tabularnewline
p-value & (0.0028) & (0) & (0) \tabularnewline
hapiness;parentalexpectations & -0.353 & -0.3318 & -0.257 \tabularnewline
p-value & (0) & (1e-04) & (0) \tabularnewline
gender;doubsaboutactions & 0.1323 & 0.1278 & 0.1101 \tabularnewline
p-value & (0.1151) & (0.1282) & (0.1278) \tabularnewline
gender;belonging & -0.2061 & -0.2284 & -0.1925 \tabularnewline
p-value & (0.0136) & (0.0061) & (0.0065) \tabularnewline
gender;parentalexpectations & 0.1323 & 0.1278 & 0.1101 \tabularnewline
p-value & (0.1151) & (0.1282) & (0.1278) \tabularnewline
doubsaboutactions;belonging & -0.2531 & -0.3138 & -0.2368 \tabularnewline
p-value & (0.0023) & (1e-04) & (1e-04) \tabularnewline
doubsaboutactions;parentalexpectations & 1 & 1 & 1 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
belonging;parentalexpectations & -0.2531 & -0.3138 & -0.2368 \tabularnewline
p-value & (0.0023) & (1e-04) & (1e-04) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108007&T=2

[TABLE]
[ROW][C]Correlations for all pairs of data series with p-values[/C][/ROW]
[ROW][C]pair[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]popularity;hapiness[/C][C]0.0783[/C][C]0.0158[/C][C]0.0065[/C][/ROW]
[ROW][C]p-value[/C][C](0.3524)[/C][C](0.8512)[/C][C](0.9166)[/C][/ROW]
[ROW][C]popularity;gender[/C][C]-0.1917[/C][C]-0.1796[/C][C]-0.1539[/C][/ROW]
[ROW][C]p-value[/C][C](0.0218)[/C][C](0.0318)[/C][C](0.0323)[/C][/ROW]
[ROW][C]popularity;doubsaboutactions[/C][C]-0.1294[/C][C]-0.1229[/C][C]-0.0894[/C][/ROW]
[ROW][C]p-value[/C][C](0.1234)[/C][C](0.1435)[/C][C](0.1494)[/C][/ROW]
[ROW][C]popularity;belonging[/C][C]0.286[/C][C]0.3058[/C][C]0.2262[/C][/ROW]
[ROW][C]p-value[/C][C](5e-04)[/C][C](2e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]popularity;parentalexpectations[/C][C]-0.1294[/C][C]-0.1229[/C][C]-0.0894[/C][/ROW]
[ROW][C]p-value[/C][C](0.1234)[/C][C](0.1435)[/C][C](0.1494)[/C][/ROW]
[ROW][C]hapiness;gender[/C][C]-0.1643[/C][C]-0.1534[/C][C]-0.1327[/C][/ROW]
[ROW][C]p-value[/C][C](0.0499)[/C][C](0.0674)[/C][C](0.0676)[/C][/ROW]
[ROW][C]hapiness;doubsaboutactions[/C][C]-0.353[/C][C]-0.3318[/C][C]-0.257[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](0)[/C][/ROW]
[ROW][C]hapiness;belonging[/C][C]0.2482[/C][C]0.3755[/C][C]0.2779[/C][/ROW]
[ROW][C]p-value[/C][C](0.0028)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]hapiness;parentalexpectations[/C][C]-0.353[/C][C]-0.3318[/C][C]-0.257[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](0)[/C][/ROW]
[ROW][C]gender;doubsaboutactions[/C][C]0.1323[/C][C]0.1278[/C][C]0.1101[/C][/ROW]
[ROW][C]p-value[/C][C](0.1151)[/C][C](0.1282)[/C][C](0.1278)[/C][/ROW]
[ROW][C]gender;belonging[/C][C]-0.2061[/C][C]-0.2284[/C][C]-0.1925[/C][/ROW]
[ROW][C]p-value[/C][C](0.0136)[/C][C](0.0061)[/C][C](0.0065)[/C][/ROW]
[ROW][C]gender;parentalexpectations[/C][C]0.1323[/C][C]0.1278[/C][C]0.1101[/C][/ROW]
[ROW][C]p-value[/C][C](0.1151)[/C][C](0.1282)[/C][C](0.1278)[/C][/ROW]
[ROW][C]doubsaboutactions;belonging[/C][C]-0.2531[/C][C]-0.3138[/C][C]-0.2368[/C][/ROW]
[ROW][C]p-value[/C][C](0.0023)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]doubsaboutactions;parentalexpectations[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]belonging;parentalexpectations[/C][C]-0.2531[/C][C]-0.3138[/C][C]-0.2368[/C][/ROW]
[ROW][C]p-value[/C][C](0.0023)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108007&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108007&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
popularity;hapiness0.07830.01580.0065
p-value(0.3524)(0.8512)(0.9166)
popularity;gender-0.1917-0.1796-0.1539
p-value(0.0218)(0.0318)(0.0323)
popularity;doubsaboutactions-0.1294-0.1229-0.0894
p-value(0.1234)(0.1435)(0.1494)
popularity;belonging0.2860.30580.2262
p-value(5e-04)(2e-04)(2e-04)
popularity;parentalexpectations-0.1294-0.1229-0.0894
p-value(0.1234)(0.1435)(0.1494)
hapiness;gender-0.1643-0.1534-0.1327
p-value(0.0499)(0.0674)(0.0676)
hapiness;doubsaboutactions-0.353-0.3318-0.257
p-value(0)(1e-04)(0)
hapiness;belonging0.24820.37550.2779
p-value(0.0028)(0)(0)
hapiness;parentalexpectations-0.353-0.3318-0.257
p-value(0)(1e-04)(0)
gender;doubsaboutactions0.13230.12780.1101
p-value(0.1151)(0.1282)(0.1278)
gender;belonging-0.2061-0.2284-0.1925
p-value(0.0136)(0.0061)(0.0065)
gender;parentalexpectations0.13230.12780.1101
p-value(0.1151)(0.1282)(0.1278)
doubsaboutactions;belonging-0.2531-0.3138-0.2368
p-value(0.0023)(1e-04)(1e-04)
doubsaboutactions;parentalexpectations111
p-value(0)(0)(0)
belonging;parentalexpectations-0.2531-0.3138-0.2368
p-value(0.0023)(1e-04)(1e-04)



Parameters (Session):
par1 = kendall ;
Parameters (R input):
par1 = kendall ;
R code (references can be found in the software module):
panel.tau <- function(x, y, digits=2, prefix='', cex.cor)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
rr <- cor.test(x, y, method=par1)
r <- round(rr$p.value,2)
txt <- format(c(r, 0.123456789), digits=digits)[1]
txt <- paste(prefix, txt, sep='')
if(missing(cex.cor)) cex <- 0.5/strwidth(txt)
text(0.5, 0.5, txt, cex = cex)
}
panel.hist <- function(x, ...)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(usr[1:2], 0, 1.5) )
h <- hist(x, plot = FALSE)
breaks <- h$breaks; nB <- length(breaks)
y <- h$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
n
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$estimate,3))
}
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,'Correlations for all pairs of data series with p-values',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'Pearson r',1,TRUE)
a<-table.element(a,'Spearman rho',1,TRUE)
a<-table.element(a,'Kendall tau',1,TRUE)
a<-table.row.end(a)
cor.test(y[1,],y[2,],method=par1)
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='')
a<-table.element(a,dum,header=TRUE)
rp <- cor.test(y[i,],y[j,],method='pearson')
a<-table.element(a,round(rp$estimate,4))
rs <- cor.test(y[i,],y[j,],method='spearman')
a<-table.element(a,round(rs$estimate,4))
rk <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,round(rk$estimate,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=T)
a<-table.element(a,paste('(',round(rp$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rs$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rk$p.value,4),')',sep=''))
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')