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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 computationThu, 24 Nov 2011 07:37:04 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/24/t1322138286cjs1sk4kspyjff5.htm/, Retrieved Thu, 28 Mar 2024 10:56:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=146677, Retrieved Thu, 28 Mar 2024 10:56:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [] [2011-11-24 12:37:04] [05300ca098a536dd63793e3fbb62faf1] [Current]
-    D    [Kendall tau Correlation Matrix] [] [2011-12-20 08:56:34] [be8fee7ddc6548b264a38e197c691443]
- RMP       [Multiple Regression] [] [2011-12-20 09:25:32] [be8fee7ddc6548b264a38e197c691443]
- RMP       [Recursive Partitioning (Regression Trees)] [] [2011-12-20 09:41:38] [be8fee7ddc6548b264a38e197c691443]
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Dataseries X:
2	24	14	11	12	24	26
2	25	11	7	8	25	23
2	17	6	17	8	30	25
1	18	12	10	8	19	23
2	18	8	12	9	22	19
2	16	10	12	7	22	29
2	20	10	11	4	25	25
2	16	11	11	11	23	21
2	18	16	12	7	17	22
2	17	11	13	7	21	25
1	23	13	14	12	19	24
2	30	12	16	10	19	18
1	23	8	11	10	15	22
2	18	12	10	8	16	15
2	15	11	11	8	23	22
1	12	4	15	4	27	28
1	21	9	9	9	22	20
2	15	8	11	8	14	12
1	20	8	17	7	22	24
2	31	14	17	11	23	20
1	27	15	11	9	23	21
2	34	16	18	11	21	20
2	21	9	14	13	19	21
2	31	14	10	8	18	23
1	19	11	11	8	20	28
2	16	8	15	9	23	24
1	20	9	15	6	25	24
2	21	9	13	9	19	24
2	22	9	16	9	24	23
1	17	9	13	6	22	23
2	24	10	9	6	25	29
1	25	16	18	16	26	24
2	26	11	18	5	29	18
2	25	8	12	7	32	25
1	17	9	17	9	25	21
1	32	16	9	6	29	26
1	33	11	9	6	28	22
1	13	16	12	5	17	22
2	32	12	18	12	28	22
1	25	12	12	7	29	23
1	29	14	18	10	26	30
2	22	9	14	9	25	23
1	18	10	15	8	14	17
1	17	9	16	5	25	23
2	20	10	10	8	26	23
2	15	12	11	8	20	25
2	20	14	14	10	18	24
2	33	14	9	6	32	24
2	29	10	12	8	25	23
1	23	14	17	7	25	21
2	26	16	5	4	23	24
1	18	9	12	8	21	24
1	20	10	12	8	20	28
2	11	6	6	4	15	16
1	28	8	24	20	30	20
2	26	13	12	8	24	29
2	22	10	12	8	26	27
2	17	8	14	6	24	22
1	12	7	7	4	22	28
2	14	15	13	8	14	16
1	17	9	12	9	24	25
1	21	10	13	6	24	24
2	19	12	14	7	24	28
2	18	13	8	9	24	24
2	10	10	11	5	19	23
1	29	11	9	5	31	30
2	31	8	11	8	22	24
1	19	9	13	8	27	21
2	9	13	10	6	19	25
1	20	11	11	8	25	25
1	28	8	12	7	20	22
2	19	9	9	7	21	23
2	30	9	15	9	27	26
1	29	15	18	11	23	23
1	26	9	15	6	25	25
2	23	10	12	8	20	21
2	13	14	13	6	21	25
2	21	12	14	9	22	24
1	19	12	10	8	23	29
1	28	11	13	6	25	22
1	23	14	13	10	25	27
1	18	6	11	8	17	26
2	21	12	13	8	19	22
1	20	8	16	10	25	24
2	23	14	8	5	19	27
2	21	11	16	7	20	24
1	21	10	11	5	26	24
2	15	14	9	8	23	29
2	28	12	16	14	27	22
2	19	10	12	7	17	21
2	26	14	14	8	17	24
2	10	5	8	6	19	24
2	16	11	9	5	17	23
2	22	10	15	6	22	20
2	19	9	11	10	21	27
2	31	10	21	12	32	26
2	31	16	14	9	21	25
2	29	13	18	12	21	21
1	19	9	12	7	18	21
1	22	10	13	8	18	19
2	23	10	15	10	23	21
1	15	7	12	6	19	21
2	20	9	19	10	20	16
1	18	8	15	10	21	22
2	23	14	11	10	20	29
1	25	14	11	5	17	15
2	21	8	10	7	18	17
1	24	9	13	10	19	15
1	25	14	15	11	22	21
2	17	14	12	6	15	21
2	13	8	12	7	14	19
2	28	8	16	12	18	24
2	21	8	9	11	24	20
1	25	7	18	11	35	17
2	9	6	8	11	29	23
1	16	8	13	5	21	24
2	19	6	17	8	25	14
2	17	11	9	6	20	19
2	25	14	15	9	22	24
2	20	11	8	4	13	13
2	29	11	7	4	26	22
2	14	11	12	7	17	16
2	22	14	14	11	25	19
2	15	8	6	6	20	25
2	19	20	8	7	19	25
2	20	11	17	8	21	23
1	15	8	10	4	22	24
2	20	11	11	8	24	26
2	18	10	14	9	21	26
2	33	14	11	8	26	25
1	22	11	13	11	24	18
1	16	9	12	8	16	21
2	17	9	11	5	23	26
1	16	8	9	4	18	23
1	21	10	12	8	16	23
2	26	13	20	10	26	22
1	18	13	12	6	19	20
1	18	12	13	9	21	13
2	17	8	12	9	21	24
2	22	13	12	13	22	15
1	30	14	9	9	23	14
2	30	12	15	10	29	22
1	24	14	24	20	21	10
2	21	15	7	5	21	24
1	21	13	17	11	23	22
2	29	16	11	6	27	24
2	31	9	17	9	25	19
1	20	9	11	7	21	20
1	16	9	12	9	10	13
1	22	8	14	10	20	20
2	20	7	11	9	26	22
2	28	16	16	8	24	24
1	38	11	21	7	29	29
2	22	9	14	6	19	12
2	20	11	20	13	24	20
2	17	9	13	6	19	21
2	28	14	11	8	24	24
2	22	13	15	10	22	22
2	31	16	19	16	17	20




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'AstonUniversity' @ aston.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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146677&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146677&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146677&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'AstonUniversity' @ aston.wessa.net







Correlations for all pairs of data series (method=pearson)
GENConMisDoubtsactparexpparcritpersstandorg
GEN10.0060.127-0.1050.004-0.0410.014
ConMis0.00610.3950.3290.3110.4250.054
Doubtsact0.1270.39510.0270.154-0.0320.07
parexp-0.1050.3290.02710.5930.244-0.155
parcrit0.0040.3110.1540.59310.131-0.203
persstand-0.0410.425-0.0320.2440.13110.352
org0.0140.0540.07-0.155-0.2030.3521

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & GEN & ConMis & Doubtsact & parexp & parcrit & persstand & org \tabularnewline
GEN & 1 & 0.006 & 0.127 & -0.105 & 0.004 & -0.041 & 0.014 \tabularnewline
ConMis & 0.006 & 1 & 0.395 & 0.329 & 0.311 & 0.425 & 0.054 \tabularnewline
Doubtsact & 0.127 & 0.395 & 1 & 0.027 & 0.154 & -0.032 & 0.07 \tabularnewline
parexp & -0.105 & 0.329 & 0.027 & 1 & 0.593 & 0.244 & -0.155 \tabularnewline
parcrit & 0.004 & 0.311 & 0.154 & 0.593 & 1 & 0.131 & -0.203 \tabularnewline
persstand & -0.041 & 0.425 & -0.032 & 0.244 & 0.131 & 1 & 0.352 \tabularnewline
org & 0.014 & 0.054 & 0.07 & -0.155 & -0.203 & 0.352 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146677&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]GEN[/C][C]ConMis[/C][C]Doubtsact[/C][C]parexp[/C][C]parcrit[/C][C]persstand[/C][C]org[/C][/ROW]
[ROW][C]GEN[/C][C]1[/C][C]0.006[/C][C]0.127[/C][C]-0.105[/C][C]0.004[/C][C]-0.041[/C][C]0.014[/C][/ROW]
[ROW][C]ConMis[/C][C]0.006[/C][C]1[/C][C]0.395[/C][C]0.329[/C][C]0.311[/C][C]0.425[/C][C]0.054[/C][/ROW]
[ROW][C]Doubtsact[/C][C]0.127[/C][C]0.395[/C][C]1[/C][C]0.027[/C][C]0.154[/C][C]-0.032[/C][C]0.07[/C][/ROW]
[ROW][C]parexp[/C][C]-0.105[/C][C]0.329[/C][C]0.027[/C][C]1[/C][C]0.593[/C][C]0.244[/C][C]-0.155[/C][/ROW]
[ROW][C]parcrit[/C][C]0.004[/C][C]0.311[/C][C]0.154[/C][C]0.593[/C][C]1[/C][C]0.131[/C][C]-0.203[/C][/ROW]
[ROW][C]persstand[/C][C]-0.041[/C][C]0.425[/C][C]-0.032[/C][C]0.244[/C][C]0.131[/C][C]1[/C][C]0.352[/C][/ROW]
[ROW][C]org[/C][C]0.014[/C][C]0.054[/C][C]0.07[/C][C]-0.155[/C][C]-0.203[/C][C]0.352[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146677&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146677&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)
GENConMisDoubtsactparexpparcritpersstandorg
GEN10.0060.127-0.1050.004-0.0410.014
ConMis0.00610.3950.3290.3110.4250.054
Doubtsact0.1270.39510.0270.154-0.0320.07
parexp-0.1050.3290.02710.5930.244-0.155
parcrit0.0040.3110.1540.59310.131-0.203
persstand-0.0410.425-0.0320.2440.13110.352
org0.0140.0540.07-0.155-0.2030.3521







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
GEN;ConMis0.00610.01370.0115
p-value(0.9394)(0.864)(0.8634)
GEN;Doubtsact0.12730.13290.1144
p-value(0.1098)(0.095)(0.0949)
GEN;parexp-0.1048-0.0869-0.0741
p-value(0.1887)(0.2763)(0.275)
GEN;parcrit0.00390.05120.0443
p-value(0.9612)(0.5214)(0.5197)
GEN;persstand-0.0405-0.0447-0.0378
p-value(0.6119)(0.5762)(0.5745)
GEN;org0.01440.03090.0263
p-value(0.8571)(0.6992)(0.6979)
ConMis;Doubtsact0.39530.39490.3021
p-value(0)(0)(0)
ConMis;parexp0.32880.28420.2144
p-value(0)(3e-04)(2e-04)
ConMis;parcrit0.31090.33090.2526
p-value(1e-04)(0)(0)
ConMis;persstand0.4250.40770.3013
p-value(0)(0)(0)
ConMis;org0.05410.00580.0018
p-value(0.4983)(0.9427)(0.9749)
Doubtsact;parexp0.02720.02130.0124
p-value(0.7332)(0.7897)(0.8314)
Doubtsact;parcrit0.15430.12050.0884
p-value(0.0521)(0.1304)(0.1357)
Doubtsact;persstand-0.03240.00270.002
p-value(0.6847)(0.9734)(0.9724)
Doubtsact;org0.06980.08150.0587
p-value(0.3817)(0.3068)(0.314)
parexp;parcrit0.59320.48210.3775
p-value(0)(0)(0)
parexp;persstand0.24360.19870.1512
p-value(0.002)(0.0121)(0.0084)
parexp;org-0.1549-0.1805-0.1349
p-value(0.0512)(0.0228)(0.0196)
parcrit;persstand0.13130.11590.085
p-value(0.099)(0.1459)(0.1439)
parcrit;org-0.203-0.189-0.1383
p-value(0.0103)(0.0171)(0.0182)
persstand;org0.35220.3090.2242
p-value(0)(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
GEN;ConMis & 0.0061 & 0.0137 & 0.0115 \tabularnewline
p-value & (0.9394) & (0.864) & (0.8634) \tabularnewline
GEN;Doubtsact & 0.1273 & 0.1329 & 0.1144 \tabularnewline
p-value & (0.1098) & (0.095) & (0.0949) \tabularnewline
GEN;parexp & -0.1048 & -0.0869 & -0.0741 \tabularnewline
p-value & (0.1887) & (0.2763) & (0.275) \tabularnewline
GEN;parcrit & 0.0039 & 0.0512 & 0.0443 \tabularnewline
p-value & (0.9612) & (0.5214) & (0.5197) \tabularnewline
GEN;persstand & -0.0405 & -0.0447 & -0.0378 \tabularnewline
p-value & (0.6119) & (0.5762) & (0.5745) \tabularnewline
GEN;org & 0.0144 & 0.0309 & 0.0263 \tabularnewline
p-value & (0.8571) & (0.6992) & (0.6979) \tabularnewline
ConMis;Doubtsact & 0.3953 & 0.3949 & 0.3021 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
ConMis;parexp & 0.3288 & 0.2842 & 0.2144 \tabularnewline
p-value & (0) & (3e-04) & (2e-04) \tabularnewline
ConMis;parcrit & 0.3109 & 0.3309 & 0.2526 \tabularnewline
p-value & (1e-04) & (0) & (0) \tabularnewline
ConMis;persstand & 0.425 & 0.4077 & 0.3013 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
ConMis;org & 0.0541 & 0.0058 & 0.0018 \tabularnewline
p-value & (0.4983) & (0.9427) & (0.9749) \tabularnewline
Doubtsact;parexp & 0.0272 & 0.0213 & 0.0124 \tabularnewline
p-value & (0.7332) & (0.7897) & (0.8314) \tabularnewline
Doubtsact;parcrit & 0.1543 & 0.1205 & 0.0884 \tabularnewline
p-value & (0.0521) & (0.1304) & (0.1357) \tabularnewline
Doubtsact;persstand & -0.0324 & 0.0027 & 0.002 \tabularnewline
p-value & (0.6847) & (0.9734) & (0.9724) \tabularnewline
Doubtsact;org & 0.0698 & 0.0815 & 0.0587 \tabularnewline
p-value & (0.3817) & (0.3068) & (0.314) \tabularnewline
parexp;parcrit & 0.5932 & 0.4821 & 0.3775 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
parexp;persstand & 0.2436 & 0.1987 & 0.1512 \tabularnewline
p-value & (0.002) & (0.0121) & (0.0084) \tabularnewline
parexp;org & -0.1549 & -0.1805 & -0.1349 \tabularnewline
p-value & (0.0512) & (0.0228) & (0.0196) \tabularnewline
parcrit;persstand & 0.1313 & 0.1159 & 0.085 \tabularnewline
p-value & (0.099) & (0.1459) & (0.1439) \tabularnewline
parcrit;org & -0.203 & -0.189 & -0.1383 \tabularnewline
p-value & (0.0103) & (0.0171) & (0.0182) \tabularnewline
persstand;org & 0.3522 & 0.309 & 0.2242 \tabularnewline
p-value & (0) & (1e-04) & (1e-04) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146677&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]GEN;ConMis[/C][C]0.0061[/C][C]0.0137[/C][C]0.0115[/C][/ROW]
[ROW][C]p-value[/C][C](0.9394)[/C][C](0.864)[/C][C](0.8634)[/C][/ROW]
[ROW][C]GEN;Doubtsact[/C][C]0.1273[/C][C]0.1329[/C][C]0.1144[/C][/ROW]
[ROW][C]p-value[/C][C](0.1098)[/C][C](0.095)[/C][C](0.0949)[/C][/ROW]
[ROW][C]GEN;parexp[/C][C]-0.1048[/C][C]-0.0869[/C][C]-0.0741[/C][/ROW]
[ROW][C]p-value[/C][C](0.1887)[/C][C](0.2763)[/C][C](0.275)[/C][/ROW]
[ROW][C]GEN;parcrit[/C][C]0.0039[/C][C]0.0512[/C][C]0.0443[/C][/ROW]
[ROW][C]p-value[/C][C](0.9612)[/C][C](0.5214)[/C][C](0.5197)[/C][/ROW]
[ROW][C]GEN;persstand[/C][C]-0.0405[/C][C]-0.0447[/C][C]-0.0378[/C][/ROW]
[ROW][C]p-value[/C][C](0.6119)[/C][C](0.5762)[/C][C](0.5745)[/C][/ROW]
[ROW][C]GEN;org[/C][C]0.0144[/C][C]0.0309[/C][C]0.0263[/C][/ROW]
[ROW][C]p-value[/C][C](0.8571)[/C][C](0.6992)[/C][C](0.6979)[/C][/ROW]
[ROW][C]ConMis;Doubtsact[/C][C]0.3953[/C][C]0.3949[/C][C]0.3021[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]ConMis;parexp[/C][C]0.3288[/C][C]0.2842[/C][C]0.2144[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](3e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]ConMis;parcrit[/C][C]0.3109[/C][C]0.3309[/C][C]0.2526[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]ConMis;persstand[/C][C]0.425[/C][C]0.4077[/C][C]0.3013[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]ConMis;org[/C][C]0.0541[/C][C]0.0058[/C][C]0.0018[/C][/ROW]
[ROW][C]p-value[/C][C](0.4983)[/C][C](0.9427)[/C][C](0.9749)[/C][/ROW]
[ROW][C]Doubtsact;parexp[/C][C]0.0272[/C][C]0.0213[/C][C]0.0124[/C][/ROW]
[ROW][C]p-value[/C][C](0.7332)[/C][C](0.7897)[/C][C](0.8314)[/C][/ROW]
[ROW][C]Doubtsact;parcrit[/C][C]0.1543[/C][C]0.1205[/C][C]0.0884[/C][/ROW]
[ROW][C]p-value[/C][C](0.0521)[/C][C](0.1304)[/C][C](0.1357)[/C][/ROW]
[ROW][C]Doubtsact;persstand[/C][C]-0.0324[/C][C]0.0027[/C][C]0.002[/C][/ROW]
[ROW][C]p-value[/C][C](0.6847)[/C][C](0.9734)[/C][C](0.9724)[/C][/ROW]
[ROW][C]Doubtsact;org[/C][C]0.0698[/C][C]0.0815[/C][C]0.0587[/C][/ROW]
[ROW][C]p-value[/C][C](0.3817)[/C][C](0.3068)[/C][C](0.314)[/C][/ROW]
[ROW][C]parexp;parcrit[/C][C]0.5932[/C][C]0.4821[/C][C]0.3775[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]parexp;persstand[/C][C]0.2436[/C][C]0.1987[/C][C]0.1512[/C][/ROW]
[ROW][C]p-value[/C][C](0.002)[/C][C](0.0121)[/C][C](0.0084)[/C][/ROW]
[ROW][C]parexp;org[/C][C]-0.1549[/C][C]-0.1805[/C][C]-0.1349[/C][/ROW]
[ROW][C]p-value[/C][C](0.0512)[/C][C](0.0228)[/C][C](0.0196)[/C][/ROW]
[ROW][C]parcrit;persstand[/C][C]0.1313[/C][C]0.1159[/C][C]0.085[/C][/ROW]
[ROW][C]p-value[/C][C](0.099)[/C][C](0.1459)[/C][C](0.1439)[/C][/ROW]
[ROW][C]parcrit;org[/C][C]-0.203[/C][C]-0.189[/C][C]-0.1383[/C][/ROW]
[ROW][C]p-value[/C][C](0.0103)[/C][C](0.0171)[/C][C](0.0182)[/C][/ROW]
[ROW][C]persstand;org[/C][C]0.3522[/C][C]0.309[/C][C]0.2242[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146677&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146677&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
GEN;ConMis0.00610.01370.0115
p-value(0.9394)(0.864)(0.8634)
GEN;Doubtsact0.12730.13290.1144
p-value(0.1098)(0.095)(0.0949)
GEN;parexp-0.1048-0.0869-0.0741
p-value(0.1887)(0.2763)(0.275)
GEN;parcrit0.00390.05120.0443
p-value(0.9612)(0.5214)(0.5197)
GEN;persstand-0.0405-0.0447-0.0378
p-value(0.6119)(0.5762)(0.5745)
GEN;org0.01440.03090.0263
p-value(0.8571)(0.6992)(0.6979)
ConMis;Doubtsact0.39530.39490.3021
p-value(0)(0)(0)
ConMis;parexp0.32880.28420.2144
p-value(0)(3e-04)(2e-04)
ConMis;parcrit0.31090.33090.2526
p-value(1e-04)(0)(0)
ConMis;persstand0.4250.40770.3013
p-value(0)(0)(0)
ConMis;org0.05410.00580.0018
p-value(0.4983)(0.9427)(0.9749)
Doubtsact;parexp0.02720.02130.0124
p-value(0.7332)(0.7897)(0.8314)
Doubtsact;parcrit0.15430.12050.0884
p-value(0.0521)(0.1304)(0.1357)
Doubtsact;persstand-0.03240.00270.002
p-value(0.6847)(0.9734)(0.9724)
Doubtsact;org0.06980.08150.0587
p-value(0.3817)(0.3068)(0.314)
parexp;parcrit0.59320.48210.3775
p-value(0)(0)(0)
parexp;persstand0.24360.19870.1512
p-value(0.002)(0.0121)(0.0084)
parexp;org-0.1549-0.1805-0.1349
p-value(0.0512)(0.0228)(0.0196)
parcrit;persstand0.13130.11590.085
p-value(0.099)(0.1459)(0.1439)
parcrit;org-0.203-0.189-0.1383
p-value(0.0103)(0.0171)(0.0182)
persstand;org0.35220.3090.2242
p-value(0)(1e-04)(1e-04)



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')