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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 computationSun, 19 Dec 2010 14:35:42 +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/19/t1292769241coed48vomz2uzhg.htm/, Retrieved Sun, 05 May 2024 02:24:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112437, Retrieved Sun, 05 May 2024 02:24:29 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact64
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
-   PD  [Multiple Regression] [WS7 first regress...] [2010-11-22 18:18:06] [49c7a512c56172bc46ae7e93e5b58c1c]
-    D    [Multiple Regression] [Paper Multiple Re...] [2010-12-18 14:35:02] [49c7a512c56172bc46ae7e93e5b58c1c]
- RM D        [Kendall tau Correlation Matrix] [Paper Kendall tau...] [2010-12-19 14:35:42] [628a2d48b4bd249e4129ba023c5511b0] [Current]
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Dataseries X:
1	41	25	15	9	3
1	38	25	15	9	4
1	37	19	14	9	4
1	42	18	10	8	4
1	40	23	18	15	3
1	43	25	14	9	4
1	40	23	11	11	4
1	45	30	17	6	5
1	45	32	21	10	4
1	44	25	7	11	4
1	42	26	18	16	4
1	41	35	18	7	4
1	38	20	12	10	4
1	38	21	9	9	4
1	46	17	11	6	5
1	42	27	16	12	4
1	46	25	12	10	4
1	43	18	14	14	5
1	38	22	13	9	4
1	39	23	17	14	4
1	40	25	13	14	3
1	37	19	13	9	2
1	41	20	12	8	4
1	46	26	12	10	4
1	37	22	9	9	3
1	39	25	17	9	4
1	44	29	18	11	5
1	38	22	12	10	2
1	38	32	12	8	0
1	38	23	9	14	4
1	33	18	13	10	3
1	43	26	11	14	4
1	41	14	13	15	2
1	45	25	11	10	5
1	38	23	15	10	4
1	39	24	11	11	4
1	40	21	14	10	4
1	36	17	12	16	2
1	49	29	8	6	5
1	41	25	11	11	4
1	42	25	17	14	3
1	41	25	16	9	5
1	43	21	13	11	4
1	46	23	15	8	3
1	41	25	16	8	5
1	39	25	7	11	4
1	42	24	16	16	4
1	35	21	13	12	5
1	36	22	15	14	3
1	41	20	12	10	4
1	41	22	15	10	3
1	36	28	18	12	4
1	46	25	17	9	4
1	44	21	15	8	4
1	43	27	11	16	2
1	40	19	12	13	5
1	40	20	14	8	3
1	39	22	10	8	4
1	44	26	11	7	4
1	38	17	12	11	2
1	39	15	6	6	4
1	41	27	15	9	5
1	39	25	14	14	3
1	40	19	16	12	4
1	44	18	16	8	4
1	42	15	11	8	4
1	46	29	15	12	5
1	44	24	12	13	4
1	37	24	13	11	4
1	39	22	14	12	2
1	40	22	12	13	3
1	42	25	17	14	3
1	37	21	11	9	3
1	33	21	13	8	2
1	35	18	9	8	4
1	42	10	12	9	2
0	36	18	10	14	2
0	44	23	9	14	4
0	45	24	11	14	4
0	47	32	9	14	4
0	40	24	16	9	4
0	48	30	24	8	5
0	45	23	11	11	5
0	41	21	12	9	4
0	34	24	8	13	2
0	38	23	5	16	2
0	37	19	10	12	3
0	48	27	15	4	5
0	39	26	10	10	4
0	34	26	18	14	4
0	35	16	12	10	2
0	41	27	13	9	3
0	43	14	11	8	4
0	41	18	12	9	3
0	39	21	7	15	2
0	36	22	17	8	4
0	46	23	10	12	4
0	42	24	12	9	4
0	42	19	10	13	2
0	45	22	7	7	3
0	39	24	13	10	4
0	45	28	9	11	4
0	48	24	9	8	5
0	35	21	11	9	2
0	38	21	14	16	4
0	42	13	8	11	4
0	36	20	11	12	3
0	37	22	11	8	4
0	38	19	12	7	3
0	43	26	20	13	4
0	35	19	8	20	2
0	36	20	11	11	4
0	33	14	15	10	2
0	39	17	12	16	4
0	45	21	12	8	3
0	35	19	11	10	4
0	38	17	9	11	3
0	36	19	8	14	3
0	42	17	12	10	3
0	41	19	13	12	4
0	35	20	16	11	3
0	43	20	11	14	3
0	40	29	9	16	4
0	46	23	11	9	4
0	44	23	11	11	5
0	35	19	13	9	3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112437&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' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112437&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112437&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'George Udny Yule' @ 72.249.76.132







Correlations for all pairs of data series (method=kendall)
GenderStudyForCareerPersonalStandardsParentalExpectationDoubtsLeaderPreference
Gender10.0560.1390.272-0.0930.119
StudyForCareer0.05610.2890.029-0.1140.372
PersonalStandards0.1390.28910.2030.0270.29
ParentalExpectation0.2720.0290.2031-0.0450.115
Doubts-0.093-0.1140.027-0.0451-0.174
LeaderPreference0.1190.3720.290.115-0.1741

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Gender & StudyForCareer & PersonalStandards & ParentalExpectation & Doubts & LeaderPreference \tabularnewline
Gender & 1 & 0.056 & 0.139 & 0.272 & -0.093 & 0.119 \tabularnewline
StudyForCareer & 0.056 & 1 & 0.289 & 0.029 & -0.114 & 0.372 \tabularnewline
PersonalStandards & 0.139 & 0.289 & 1 & 0.203 & 0.027 & 0.29 \tabularnewline
ParentalExpectation & 0.272 & 0.029 & 0.203 & 1 & -0.045 & 0.115 \tabularnewline
Doubts & -0.093 & -0.114 & 0.027 & -0.045 & 1 & -0.174 \tabularnewline
LeaderPreference & 0.119 & 0.372 & 0.29 & 0.115 & -0.174 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112437&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Gender[/C][C]StudyForCareer[/C][C]PersonalStandards[/C][C]ParentalExpectation[/C][C]Doubts[/C][C]LeaderPreference[/C][/ROW]
[ROW][C]Gender[/C][C]1[/C][C]0.056[/C][C]0.139[/C][C]0.272[/C][C]-0.093[/C][C]0.119[/C][/ROW]
[ROW][C]StudyForCareer[/C][C]0.056[/C][C]1[/C][C]0.289[/C][C]0.029[/C][C]-0.114[/C][C]0.372[/C][/ROW]
[ROW][C]PersonalStandards[/C][C]0.139[/C][C]0.289[/C][C]1[/C][C]0.203[/C][C]0.027[/C][C]0.29[/C][/ROW]
[ROW][C]ParentalExpectation[/C][C]0.272[/C][C]0.029[/C][C]0.203[/C][C]1[/C][C]-0.045[/C][C]0.115[/C][/ROW]
[ROW][C]Doubts[/C][C]-0.093[/C][C]-0.114[/C][C]0.027[/C][C]-0.045[/C][C]1[/C][C]-0.174[/C][/ROW]
[ROW][C]LeaderPreference[/C][C]0.119[/C][C]0.372[/C][C]0.29[/C][C]0.115[/C][C]-0.174[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112437&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112437&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=kendall)
GenderStudyForCareerPersonalStandardsParentalExpectationDoubtsLeaderPreference
Gender10.0560.1390.272-0.0930.119
StudyForCareer0.05610.2890.029-0.1140.372
PersonalStandards0.1390.28910.2030.0270.29
ParentalExpectation0.2720.0290.2031-0.0450.115
Doubts-0.093-0.1140.027-0.0451-0.174
LeaderPreference0.1190.3720.290.115-0.1741







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Gender;StudyForCareer0.05720.06550.0555
p-value(0.5249)(0.4659)(0.4636)
Gender;PersonalStandards0.14540.16490.1395
p-value(0.1042)(0.065)(0.0652)
Gender;ParentalExpectation0.25740.31820.2721
p-value(0.0036)(3e-04)(4e-04)
Gender;Doubts-0.1146-0.1077-0.0928
p-value(0.2013)(0.2301)(0.2287)
Gender;LeaderPreference0.10590.12870.1194
p-value(0.238)(0.1511)(0.1503)
StudyForCareer;PersonalStandards0.36950.38920.2894
p-value(0)(0)(0)
StudyForCareer;ParentalExpectation0.08530.03970.029
p-value(0.3423)(0.6589)(0.6546)
StudyForCareer;Doubts-0.1945-0.1527-0.1145
p-value(0.0291)(0.0877)(0.0798)
StudyForCareer;LeaderPreference0.46910.45830.3717
p-value(0)(0)(0)
PersonalStandards;ParentalExpectation0.32690.26710.2027
p-value(2e-04)(0.0025)(0.0017)
PersonalStandards;Doubts-0.00830.03310.0266
p-value(0.9263)(0.7126)(0.6835)
PersonalStandards;LeaderPreference0.29250.35280.2897
p-value(9e-04)(1e-04)(0)
ParentalExpectation;Doubts-0.0685-0.0514-0.0449
p-value(0.4457)(0.5673)(0.496)
ParentalExpectation;LeaderPreference0.20390.14350.1146
p-value(0.022)(0.1089)(0.1066)
Doubts;LeaderPreference-0.2433-0.2147-0.174
p-value(0.006)(0.0158)(0.0151)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Gender;StudyForCareer & 0.0572 & 0.0655 & 0.0555 \tabularnewline
p-value & (0.5249) & (0.4659) & (0.4636) \tabularnewline
Gender;PersonalStandards & 0.1454 & 0.1649 & 0.1395 \tabularnewline
p-value & (0.1042) & (0.065) & (0.0652) \tabularnewline
Gender;ParentalExpectation & 0.2574 & 0.3182 & 0.2721 \tabularnewline
p-value & (0.0036) & (3e-04) & (4e-04) \tabularnewline
Gender;Doubts & -0.1146 & -0.1077 & -0.0928 \tabularnewline
p-value & (0.2013) & (0.2301) & (0.2287) \tabularnewline
Gender;LeaderPreference & 0.1059 & 0.1287 & 0.1194 \tabularnewline
p-value & (0.238) & (0.1511) & (0.1503) \tabularnewline
StudyForCareer;PersonalStandards & 0.3695 & 0.3892 & 0.2894 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
StudyForCareer;ParentalExpectation & 0.0853 & 0.0397 & 0.029 \tabularnewline
p-value & (0.3423) & (0.6589) & (0.6546) \tabularnewline
StudyForCareer;Doubts & -0.1945 & -0.1527 & -0.1145 \tabularnewline
p-value & (0.0291) & (0.0877) & (0.0798) \tabularnewline
StudyForCareer;LeaderPreference & 0.4691 & 0.4583 & 0.3717 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PersonalStandards;ParentalExpectation & 0.3269 & 0.2671 & 0.2027 \tabularnewline
p-value & (2e-04) & (0.0025) & (0.0017) \tabularnewline
PersonalStandards;Doubts & -0.0083 & 0.0331 & 0.0266 \tabularnewline
p-value & (0.9263) & (0.7126) & (0.6835) \tabularnewline
PersonalStandards;LeaderPreference & 0.2925 & 0.3528 & 0.2897 \tabularnewline
p-value & (9e-04) & (1e-04) & (0) \tabularnewline
ParentalExpectation;Doubts & -0.0685 & -0.0514 & -0.0449 \tabularnewline
p-value & (0.4457) & (0.5673) & (0.496) \tabularnewline
ParentalExpectation;LeaderPreference & 0.2039 & 0.1435 & 0.1146 \tabularnewline
p-value & (0.022) & (0.1089) & (0.1066) \tabularnewline
Doubts;LeaderPreference & -0.2433 & -0.2147 & -0.174 \tabularnewline
p-value & (0.006) & (0.0158) & (0.0151) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112437&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]Gender;StudyForCareer[/C][C]0.0572[/C][C]0.0655[/C][C]0.0555[/C][/ROW]
[ROW][C]p-value[/C][C](0.5249)[/C][C](0.4659)[/C][C](0.4636)[/C][/ROW]
[ROW][C]Gender;PersonalStandards[/C][C]0.1454[/C][C]0.1649[/C][C]0.1395[/C][/ROW]
[ROW][C]p-value[/C][C](0.1042)[/C][C](0.065)[/C][C](0.0652)[/C][/ROW]
[ROW][C]Gender;ParentalExpectation[/C][C]0.2574[/C][C]0.3182[/C][C]0.2721[/C][/ROW]
[ROW][C]p-value[/C][C](0.0036)[/C][C](3e-04)[/C][C](4e-04)[/C][/ROW]
[ROW][C]Gender;Doubts[/C][C]-0.1146[/C][C]-0.1077[/C][C]-0.0928[/C][/ROW]
[ROW][C]p-value[/C][C](0.2013)[/C][C](0.2301)[/C][C](0.2287)[/C][/ROW]
[ROW][C]Gender;LeaderPreference[/C][C]0.1059[/C][C]0.1287[/C][C]0.1194[/C][/ROW]
[ROW][C]p-value[/C][C](0.238)[/C][C](0.1511)[/C][C](0.1503)[/C][/ROW]
[ROW][C]StudyForCareer;PersonalStandards[/C][C]0.3695[/C][C]0.3892[/C][C]0.2894[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]StudyForCareer;ParentalExpectation[/C][C]0.0853[/C][C]0.0397[/C][C]0.029[/C][/ROW]
[ROW][C]p-value[/C][C](0.3423)[/C][C](0.6589)[/C][C](0.6546)[/C][/ROW]
[ROW][C]StudyForCareer;Doubts[/C][C]-0.1945[/C][C]-0.1527[/C][C]-0.1145[/C][/ROW]
[ROW][C]p-value[/C][C](0.0291)[/C][C](0.0877)[/C][C](0.0798)[/C][/ROW]
[ROW][C]StudyForCareer;LeaderPreference[/C][C]0.4691[/C][C]0.4583[/C][C]0.3717[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PersonalStandards;ParentalExpectation[/C][C]0.3269[/C][C]0.2671[/C][C]0.2027[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](0.0025)[/C][C](0.0017)[/C][/ROW]
[ROW][C]PersonalStandards;Doubts[/C][C]-0.0083[/C][C]0.0331[/C][C]0.0266[/C][/ROW]
[ROW][C]p-value[/C][C](0.9263)[/C][C](0.7126)[/C][C](0.6835)[/C][/ROW]
[ROW][C]PersonalStandards;LeaderPreference[/C][C]0.2925[/C][C]0.3528[/C][C]0.2897[/C][/ROW]
[ROW][C]p-value[/C][C](9e-04)[/C][C](1e-04)[/C][C](0)[/C][/ROW]
[ROW][C]ParentalExpectation;Doubts[/C][C]-0.0685[/C][C]-0.0514[/C][C]-0.0449[/C][/ROW]
[ROW][C]p-value[/C][C](0.4457)[/C][C](0.5673)[/C][C](0.496)[/C][/ROW]
[ROW][C]ParentalExpectation;LeaderPreference[/C][C]0.2039[/C][C]0.1435[/C][C]0.1146[/C][/ROW]
[ROW][C]p-value[/C][C](0.022)[/C][C](0.1089)[/C][C](0.1066)[/C][/ROW]
[ROW][C]Doubts;LeaderPreference[/C][C]-0.2433[/C][C]-0.2147[/C][C]-0.174[/C][/ROW]
[ROW][C]p-value[/C][C](0.006)[/C][C](0.0158)[/C][C](0.0151)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112437&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112437&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
Gender;StudyForCareer0.05720.06550.0555
p-value(0.5249)(0.4659)(0.4636)
Gender;PersonalStandards0.14540.16490.1395
p-value(0.1042)(0.065)(0.0652)
Gender;ParentalExpectation0.25740.31820.2721
p-value(0.0036)(3e-04)(4e-04)
Gender;Doubts-0.1146-0.1077-0.0928
p-value(0.2013)(0.2301)(0.2287)
Gender;LeaderPreference0.10590.12870.1194
p-value(0.238)(0.1511)(0.1503)
StudyForCareer;PersonalStandards0.36950.38920.2894
p-value(0)(0)(0)
StudyForCareer;ParentalExpectation0.08530.03970.029
p-value(0.3423)(0.6589)(0.6546)
StudyForCareer;Doubts-0.1945-0.1527-0.1145
p-value(0.0291)(0.0877)(0.0798)
StudyForCareer;LeaderPreference0.46910.45830.3717
p-value(0)(0)(0)
PersonalStandards;ParentalExpectation0.32690.26710.2027
p-value(2e-04)(0.0025)(0.0017)
PersonalStandards;Doubts-0.00830.03310.0266
p-value(0.9263)(0.7126)(0.6835)
PersonalStandards;LeaderPreference0.29250.35280.2897
p-value(9e-04)(1e-04)(0)
ParentalExpectation;Doubts-0.0685-0.0514-0.0449
p-value(0.4457)(0.5673)(0.496)
ParentalExpectation;LeaderPreference0.20390.14350.1146
p-value(0.022)(0.1089)(0.1066)
Doubts;LeaderPreference-0.2433-0.2147-0.174
p-value(0.006)(0.0158)(0.0151)



Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
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')