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Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationTue, 21 Dec 2010 19:49:44 +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/21/t1292960853j0g3s6vyi540kim.htm/, Retrieved Sat, 18 May 2024 14:17:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113908, Retrieved Sat, 18 May 2024 14:17:17 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact117
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [workshop 7] [2010-12-21 19:49:44] [531024149246456e4f6d79ace2e85c12] [Current]
-    D    [Kendall tau Correlation Matrix] [onderling effect ...] [2010-12-27 12:39:51] [efd13e24149aec704f3383e33c1e842a]
-    D      [Kendall tau Correlation Matrix] [Paper_Pearson] [2010-12-28 16:10:39] [7318566ef3ec88988be4d1362d0cf918]
-   PD      [Kendall tau Correlation Matrix] [Paper_KendallTau] [2010-12-28 16:20:00] [7318566ef3ec88988be4d1362d0cf918]
-   PD    [Kendall tau Correlation Matrix] [onderling effect ...] [2010-12-27 12:49:38] [efd13e24149aec704f3383e33c1e842a]
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Dataseries X:
5	6	5	7	11	2
2	6	2	3	11	1
6	6	6	5	15	1
6	4	4	5	9	2
6	2	6	3	11	1
5	7	3	4	17	1
5	6	5	4	16	1
6	5	3	5	9	1
6	6	5	5	14	1
5	7	4	5	12	1
5	7	1	6	6	2
5	4	6	5	4	1
6	1	6	2	13	1
5	6	6	5	12	1
5	4	4	4	10	1
6	5	6	6	14	2
6	5	5	5	12	1
4	6	3	6	9	1
5	4	5	5	16	2
5	6	4	2	13	2
5	3	5	3	12	1
6	3	6	5	11	1
5	5	3	6	12	2
7	5	4	5	12	2
6	5	5	4	11	1
6	5	4	5	16	2
6	5	5	5	9	1
6	2	6	5	8	2
4	6	7	5	11	1
5	7	2	6	9	2
6	2	4	6	16	2
4	3	6	6	14	1
5	6	5	6	10	2
5	5	5	4	14	1
5	7	5	4	13	2
7	5	6	3	12	1
7	6	6	5	16	2
6	5	1	6	16	1
7	3	4	4	15	1
6	7	2	6	5	2
5	5	3	3	12	2
6	5	4	2	11	1
4	6	5	5	15	1
6	2	4	5	15	2
5	3	3	6	10	2
6	6	4	4	12	1
6	7	6	3	5	1
5	5	4	3	16	1
6	4	5	4	16	1
5	6	4	5	12	2
5	7	5	4	6	2
5	2	6	3	7	2
6	2	6	4	14	2
6	2	4	4	8	2
5	5	4	4	12	1
7	2	6	3	10	2
6	5	4	6	11	2
5	6	2	5	17	1
5	2	6	5	13	1
6	4	5	6	15	1
5	6	6	6	10	1
5	4	6	4	9	2
6	3	5	5	16	1
6	3	5	4	11	2
3	3	5	6	8	2
5	6	5	5	14	2
5	6	3	5	11	2
6	5	4	5	12	1
5	3	1	5	14	2
5	3	5	2	15	1
4	2	2	5	14	2
5	3	6	5	11	2
5	3	5	5	11	2
2	5	2	2	15	1
6	3	6	6	7	2
6	5	5	4	12	2
6	2	6	4	10	1
6	5	3	6	13	2
5	6	4	6	15	2
5	6	4	4	13	1
6	5	4	2	15	1
5	2	4	4	8	2
5	6	5	5	14	1
6	7	2	7	11	2
3	5	3	7	12	2
6	5	5	5	16	1
3	2	6	5	8	2
5	5	5	5	12	1
5	6	6	4	16	1
6	5	3	6	11	2
5	5	4	5	13	1
6	4	4	4	6	1
6	5	3	6	4	2
6	4	4	4	11	1
5	3	4	4	7	2
3	5	2	5	12	2
4	2	6	2	12	1
7	2	3	5	16	1
6	4	5	5	15	1
6	3	5	5	13	1
5	5	5	6	12	1
4	5	5	5	9	1
6	2	4	4	16	1
6	5	2	5	11	1
6	2	5	5	14	2
5	6	3	5	10	2
6	2	6	5	10	1
6	1	6	4	11	1
2	6	1	1	16	1
6	2	7	5	8	1
5	3	5	3	16	1
5	5	6	5	12	1
3	4	6	5	11	1
4	4	6	6	16	1
6	6	3	5	9	1
5	2	6	4	13	2
6	7	7	6	14	1
4	2	6	2	10	1
6	5	5	2	12	1
4	3	5	4	11	1
3	3	5	6	10	2
6	5	5	5	12	1
5	5	4	4	13	1
7	4	4	5	14	2
6	3	6	5	12	1
6	2	6	5	14	1
5	6	4	4	13	1
5	2	7	2	8	1
2	6	3	6	13	1
5	6	4	5	10	1
3	2	2	4	9	2
6	5	4	5	8	2
5	6	4	5	15	2
5	5	3	5	15	1
5	3	2	5	12	1
2	7	5	6	8	2
5	5	5	2	15	1
5	4	4	4	9	1
6	5	6	7	14	2
6	3	5	3	16	1
5	2	1	2	14	1
5	5	5	5	14	2
5	5	5	3	14	1
6	2	5	5	14	1
6	3	5	6	14	2
6	2	5	3	13	2
6	6	4	5	12	1
6	6	7	5	13	2
7	2	5	3	19	1
5	2	4	5	9	2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113908&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113908&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113908&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 time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Correlations for all pairs of data series (method=pearson)
handgebruikstilheidextravertblozenpopulariteitgeslacht
handgebruik1-0.1420.2050.0270.102-0.009
stilheid-0.1421-0.2550.2390-0.022
extravert0.205-0.2551-0.071-0.033-0.141
blozen0.0270.239-0.0711-0.1210.335
populariteit0.1020-0.033-0.1211-0.246
geslacht-0.009-0.022-0.1410.335-0.2461

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & handgebruik & stilheid & extravert & blozen & populariteit & geslacht \tabularnewline
handgebruik & 1 & -0.142 & 0.205 & 0.027 & 0.102 & -0.009 \tabularnewline
stilheid & -0.142 & 1 & -0.255 & 0.239 & 0 & -0.022 \tabularnewline
extravert & 0.205 & -0.255 & 1 & -0.071 & -0.033 & -0.141 \tabularnewline
blozen & 0.027 & 0.239 & -0.071 & 1 & -0.121 & 0.335 \tabularnewline
populariteit & 0.102 & 0 & -0.033 & -0.121 & 1 & -0.246 \tabularnewline
geslacht & -0.009 & -0.022 & -0.141 & 0.335 & -0.246 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113908&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]handgebruik[/C][C]stilheid[/C][C]extravert[/C][C]blozen[/C][C]populariteit[/C][C]geslacht[/C][/ROW]
[ROW][C]handgebruik[/C][C]1[/C][C]-0.142[/C][C]0.205[/C][C]0.027[/C][C]0.102[/C][C]-0.009[/C][/ROW]
[ROW][C]stilheid[/C][C]-0.142[/C][C]1[/C][C]-0.255[/C][C]0.239[/C][C]0[/C][C]-0.022[/C][/ROW]
[ROW][C]extravert[/C][C]0.205[/C][C]-0.255[/C][C]1[/C][C]-0.071[/C][C]-0.033[/C][C]-0.141[/C][/ROW]
[ROW][C]blozen[/C][C]0.027[/C][C]0.239[/C][C]-0.071[/C][C]1[/C][C]-0.121[/C][C]0.335[/C][/ROW]
[ROW][C]populariteit[/C][C]0.102[/C][C]0[/C][C]-0.033[/C][C]-0.121[/C][C]1[/C][C]-0.246[/C][/ROW]
[ROW][C]geslacht[/C][C]-0.009[/C][C]-0.022[/C][C]-0.141[/C][C]0.335[/C][C]-0.246[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113908&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113908&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)
handgebruikstilheidextravertblozenpopulariteitgeslacht
handgebruik1-0.1420.2050.0270.102-0.009
stilheid-0.1421-0.2550.2390-0.022
extravert0.205-0.2551-0.071-0.033-0.141
blozen0.0270.239-0.0711-0.1210.335
populariteit0.1020-0.033-0.1211-0.246
geslacht-0.009-0.022-0.1410.335-0.2461







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
handgebruik;stilheid-0.1415-0.1706-0.1415
p-value(0.084)(0.0369)(0.037)
handgebruik;extravert0.20480.12980.1084
p-value(0.0119)(0.1135)(0.1128)
handgebruik;blozen0.0268-0.0033-0.0026
p-value(0.7444)(0.9677)(0.9695)
handgebruik;populariteit0.10190.10870.0877
p-value(0.2149)(0.1856)(0.1798)
handgebruik;geslacht-0.0091-0.0136-0.0126
p-value(0.9121)(0.8691)(0.8685)
stilheid;extravert-0.2548-0.2681-0.2281
p-value(0.0017)(9e-04)(5e-04)
stilheid;blozen0.23920.2460.2002
p-value(0.0032)(0.0024)(0.0024)
stilheid;populariteit00.03180.0277
p-value(1)(0.6993)(0.6567)
stilheid;geslacht-0.022-0.0192-0.017
p-value(0.7891)(0.816)(0.8151)
extravert;blozen-0.0714-0.1003-0.0851
p-value(0.385)(0.2221)(0.201)
extravert;populariteit-0.0332-0.0399-0.0308
p-value(0.6863)(0.6279)(0.6237)
extravert;geslacht-0.1412-0.1497-0.1341
p-value(0.0848)(0.0674)(0.0676)
blozen;populariteit-0.1214-0.0991-0.0754
p-value(0.1389)(0.2275)(0.2362)
blozen;geslacht0.33540.32830.2977
p-value(0)(0)(1e-04)
populariteit;geslacht-0.2455-0.2373-0.2033
p-value(0.0025)(0.0035)(0.0038)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
handgebruik;stilheid & -0.1415 & -0.1706 & -0.1415 \tabularnewline
p-value & (0.084) & (0.0369) & (0.037) \tabularnewline
handgebruik;extravert & 0.2048 & 0.1298 & 0.1084 \tabularnewline
p-value & (0.0119) & (0.1135) & (0.1128) \tabularnewline
handgebruik;blozen & 0.0268 & -0.0033 & -0.0026 \tabularnewline
p-value & (0.7444) & (0.9677) & (0.9695) \tabularnewline
handgebruik;populariteit & 0.1019 & 0.1087 & 0.0877 \tabularnewline
p-value & (0.2149) & (0.1856) & (0.1798) \tabularnewline
handgebruik;geslacht & -0.0091 & -0.0136 & -0.0126 \tabularnewline
p-value & (0.9121) & (0.8691) & (0.8685) \tabularnewline
stilheid;extravert & -0.2548 & -0.2681 & -0.2281 \tabularnewline
p-value & (0.0017) & (9e-04) & (5e-04) \tabularnewline
stilheid;blozen & 0.2392 & 0.246 & 0.2002 \tabularnewline
p-value & (0.0032) & (0.0024) & (0.0024) \tabularnewline
stilheid;populariteit & 0 & 0.0318 & 0.0277 \tabularnewline
p-value & (1) & (0.6993) & (0.6567) \tabularnewline
stilheid;geslacht & -0.022 & -0.0192 & -0.017 \tabularnewline
p-value & (0.7891) & (0.816) & (0.8151) \tabularnewline
extravert;blozen & -0.0714 & -0.1003 & -0.0851 \tabularnewline
p-value & (0.385) & (0.2221) & (0.201) \tabularnewline
extravert;populariteit & -0.0332 & -0.0399 & -0.0308 \tabularnewline
p-value & (0.6863) & (0.6279) & (0.6237) \tabularnewline
extravert;geslacht & -0.1412 & -0.1497 & -0.1341 \tabularnewline
p-value & (0.0848) & (0.0674) & (0.0676) \tabularnewline
blozen;populariteit & -0.1214 & -0.0991 & -0.0754 \tabularnewline
p-value & (0.1389) & (0.2275) & (0.2362) \tabularnewline
blozen;geslacht & 0.3354 & 0.3283 & 0.2977 \tabularnewline
p-value & (0) & (0) & (1e-04) \tabularnewline
populariteit;geslacht & -0.2455 & -0.2373 & -0.2033 \tabularnewline
p-value & (0.0025) & (0.0035) & (0.0038) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113908&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]handgebruik;stilheid[/C][C]-0.1415[/C][C]-0.1706[/C][C]-0.1415[/C][/ROW]
[ROW][C]p-value[/C][C](0.084)[/C][C](0.0369)[/C][C](0.037)[/C][/ROW]
[ROW][C]handgebruik;extravert[/C][C]0.2048[/C][C]0.1298[/C][C]0.1084[/C][/ROW]
[ROW][C]p-value[/C][C](0.0119)[/C][C](0.1135)[/C][C](0.1128)[/C][/ROW]
[ROW][C]handgebruik;blozen[/C][C]0.0268[/C][C]-0.0033[/C][C]-0.0026[/C][/ROW]
[ROW][C]p-value[/C][C](0.7444)[/C][C](0.9677)[/C][C](0.9695)[/C][/ROW]
[ROW][C]handgebruik;populariteit[/C][C]0.1019[/C][C]0.1087[/C][C]0.0877[/C][/ROW]
[ROW][C]p-value[/C][C](0.2149)[/C][C](0.1856)[/C][C](0.1798)[/C][/ROW]
[ROW][C]handgebruik;geslacht[/C][C]-0.0091[/C][C]-0.0136[/C][C]-0.0126[/C][/ROW]
[ROW][C]p-value[/C][C](0.9121)[/C][C](0.8691)[/C][C](0.8685)[/C][/ROW]
[ROW][C]stilheid;extravert[/C][C]-0.2548[/C][C]-0.2681[/C][C]-0.2281[/C][/ROW]
[ROW][C]p-value[/C][C](0.0017)[/C][C](9e-04)[/C][C](5e-04)[/C][/ROW]
[ROW][C]stilheid;blozen[/C][C]0.2392[/C][C]0.246[/C][C]0.2002[/C][/ROW]
[ROW][C]p-value[/C][C](0.0032)[/C][C](0.0024)[/C][C](0.0024)[/C][/ROW]
[ROW][C]stilheid;populariteit[/C][C]0[/C][C]0.0318[/C][C]0.0277[/C][/ROW]
[ROW][C]p-value[/C][C](1)[/C][C](0.6993)[/C][C](0.6567)[/C][/ROW]
[ROW][C]stilheid;geslacht[/C][C]-0.022[/C][C]-0.0192[/C][C]-0.017[/C][/ROW]
[ROW][C]p-value[/C][C](0.7891)[/C][C](0.816)[/C][C](0.8151)[/C][/ROW]
[ROW][C]extravert;blozen[/C][C]-0.0714[/C][C]-0.1003[/C][C]-0.0851[/C][/ROW]
[ROW][C]p-value[/C][C](0.385)[/C][C](0.2221)[/C][C](0.201)[/C][/ROW]
[ROW][C]extravert;populariteit[/C][C]-0.0332[/C][C]-0.0399[/C][C]-0.0308[/C][/ROW]
[ROW][C]p-value[/C][C](0.6863)[/C][C](0.6279)[/C][C](0.6237)[/C][/ROW]
[ROW][C]extravert;geslacht[/C][C]-0.1412[/C][C]-0.1497[/C][C]-0.1341[/C][/ROW]
[ROW][C]p-value[/C][C](0.0848)[/C][C](0.0674)[/C][C](0.0676)[/C][/ROW]
[ROW][C]blozen;populariteit[/C][C]-0.1214[/C][C]-0.0991[/C][C]-0.0754[/C][/ROW]
[ROW][C]p-value[/C][C](0.1389)[/C][C](0.2275)[/C][C](0.2362)[/C][/ROW]
[ROW][C]blozen;geslacht[/C][C]0.3354[/C][C]0.3283[/C][C]0.2977[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](1e-04)[/C][/ROW]
[ROW][C]populariteit;geslacht[/C][C]-0.2455[/C][C]-0.2373[/C][C]-0.2033[/C][/ROW]
[ROW][C]p-value[/C][C](0.0025)[/C][C](0.0035)[/C][C](0.0038)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113908&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113908&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
handgebruik;stilheid-0.1415-0.1706-0.1415
p-value(0.084)(0.0369)(0.037)
handgebruik;extravert0.20480.12980.1084
p-value(0.0119)(0.1135)(0.1128)
handgebruik;blozen0.0268-0.0033-0.0026
p-value(0.7444)(0.9677)(0.9695)
handgebruik;populariteit0.10190.10870.0877
p-value(0.2149)(0.1856)(0.1798)
handgebruik;geslacht-0.0091-0.0136-0.0126
p-value(0.9121)(0.8691)(0.8685)
stilheid;extravert-0.2548-0.2681-0.2281
p-value(0.0017)(9e-04)(5e-04)
stilheid;blozen0.23920.2460.2002
p-value(0.0032)(0.0024)(0.0024)
stilheid;populariteit00.03180.0277
p-value(1)(0.6993)(0.6567)
stilheid;geslacht-0.022-0.0192-0.017
p-value(0.7891)(0.816)(0.8151)
extravert;blozen-0.0714-0.1003-0.0851
p-value(0.385)(0.2221)(0.201)
extravert;populariteit-0.0332-0.0399-0.0308
p-value(0.6863)(0.6279)(0.6237)
extravert;geslacht-0.1412-0.1497-0.1341
p-value(0.0848)(0.0674)(0.0676)
blozen;populariteit-0.1214-0.0991-0.0754
p-value(0.1389)(0.2275)(0.2362)
blozen;geslacht0.33540.32830.2977
p-value(0)(0)(1e-04)
populariteit;geslacht-0.2455-0.2373-0.2033
p-value(0.0025)(0.0035)(0.0038)



Parameters (Session):
par1 = pearson ;
Parameters (R input):
par1 = pearson ;
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')