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rwasp_pairs.wasp

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Kendall tau Correlation Matrix

Date of computation

Tue, 16 Dec 2014 14:37:48 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/16/t1418741509nox4bg1doe67b5l.htm/, Retrieved Thu, 16 May 2024 10:30:47 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269662, Retrieved Thu, 16 May 2024 10:30:47 +0000

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-       [Kendall tau Correlation Matrix] [] [2014-12-16 14:37:48] [37e054ac358b2aa7c2a1d0b751dfa890] [Current]

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23 26 17 27 13 12 13 13
22 20 31 30 NA NA NA NA
26 19 33 24 8 8 13 16
41 25 33 16 14 11 11 11
23 19 28 27 16 13 14 10
33 22 26 18 14 11 15 9
31 21 28 24 13 10 14 8
35 28 37 24 15 7 11 26
28 20 22 18 13 10 13 10
31 24 27 22 20 15 16 10
23 26 32 25 17 12 14 8
25 20 16 16 15 12 14 13
30 26 27 18 16 10 15 11
30 19 20 24 12 10 15 8
19 25 30 24 17 14 13 12
32 28 31 29 11 6 14 24
50 27 32 22 16 12 11 21
27 21 27 21 16 14 12 5
36 23 24 23 15 11 14 14
31 21 31 24 13 8 13 11
26 29 33 23 14 12 12 9
32 29 27 19 16 13 15 17
35 21 29 24 17 11 14 18
30 30 37 20 15 7 12 23
38 28 34 24 14 11 12 9
41 27 34 30 14 7 12 14
27 22 25 17 16 12 15 13
28 23 30 22 15 12 14 10
24 21 21 24 17 13 16 8
21 15 14 20 14 9 12 10
39 16 26 23 16 11 12 19
33 31 24 19 NA NA NA NA
28 18 24 22 15 12 14 11
47 25 25 24 16 15 16 16
26 25 33 20 16 12 15 12
25 15 26 24 10 6 12 11
34 24 23 26 8 5 14 11
30 20 27 24 17 13 13 10
30 24 31 24 14 11 14 13
25 28 31 24 10 6 16 14
19 15 15 21 14 12 12 8
28 20 26 22 12 10 14 11
39 33 27 29 16 6 15 11
20 13 13 23 16 12 13 13
30 21 32 22 16 11 16 15
31 24 27 25 8 6 16 15
19 23 23 23 16 12 12 16
25 21 24 24 15 12 12 12
52 33 41 30 8 8 16 12
33 24 37 24 13 10 12 17
22 23 23 24 14 11 15 14
32 20 30 20 13 7 12 15
17 14 17 16 16 12 13 12
31 25 26 27 19 13 12 13
20 34 19 13 19 14 14 7
29 22 35 29 14 12 14 8
37 25 22 27 15 6 11 16
21 21 27 24 13 14 10 20
23 21 21 24 10 10 12 14
30 21 28 23 16 12 11 10
21 24 24 22 15 11 16 16
24 22 32 26 11 10 14 11
40 28 39 26 9 7 14 26
20 18 18 21 16 12 15 9
33 23 31 23 12 7 15 15
20 16 19 20 12 12 14 12
26 24 30 28 14 12 13 21
22 27 37 29 14 10 11 20
32 18 20 16 13 10 16 20
13 11 15 25 15 12 12 10
28 26 34 28 17 12 15 15
32 26 25 24 14 12 14 10
27 23 22 24 9 10 14 9
32 20 34 24 NA NA NA NA
23 20 29 12 7 5 13 17
28 25 24 22 13 10 6 10
23 22 33 22 15 10 12 19
29 29 29 24 12 12 12 13
26 22 23 26 15 11 14 8
15 19 25 24 14 9 14 11
14 21 17 26 16 12 15 9
19 25 28 22 14 11 11 12
19 17 20 23 13 10 13 10
26 27 23 29 16 12 14 9
33 21 18 16 13 10 16 14
35 23 35 18 16 9 13 14
28 22 23 22 16 11 14 10
25 21 16 23 16 12 16 8
41 29 32 30 10 7 11 13
28 15 22 24 12 11 13 9
25 23 34 21 12 12 13 14
26 18 23 23 12 6 15 8
41 26 36 14 12 9 12 16
28 23 24 25 19 15 13 14
26 18 21 17 14 10 12 14
24 21 21 24 13 11 14 8
32 16 21 23 16 12 14 11
25 21 28 22 15 12 16 11
22 23 25 16 12 12 15 13
29 21 29 22 8 11 14 12
36 27 34 30 10 9 13 13
40 23 25 25 16 11 14 9
27 15 23 21 16 12 15 10
35 19 33 22 18 14 12 11
18 24 26 23 12 8 7 13
36 24 27 24 16 10 12 17
27 22 33 22 10 9 15 15
31 24 30 21 12 9 13 14
16 17 22 26 11 10 11 10
26 28 28 24 15 12 14 15
20 25 32 27 7 11 13 14

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269662&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269662&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269662&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	2 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Correlations for all pairs of data series (method=kendall)
	anderen	positief	negatief	organisatie	CONFSTATTOT	CONFSOFTTOT	STRESSTOT	CESDTOT
anderen	1	0.274	0.299	0.045	0.004	-0.199	0.024	0.181
positief	0.274	1	0.377	0.194	-0.003	-0.076	-0.019	0.204
negatief	0.299	0.377	1	0.148	-0.108	-0.166	-0.122	0.298
organisatie	0.045	0.194	0.148	1	-0.082	-0.082	-0.05	-0.009
CONFSTATTOT	0.004	-0.003	-0.108	-0.082	1	0.536	0.066	-0.109
CONFSOFTTOT	-0.199	-0.076	-0.166	-0.082	0.536	1	0.076	-0.211
STRESSTOT	0.024	-0.019	-0.122	-0.05	0.066	0.076	1	-0.126
CESDTOT	0.181	0.204	0.298	-0.009	-0.109	-0.211	-0.126	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & anderen & positief & negatief & organisatie & CONFSTATTOT & CONFSOFTTOT & STRESSTOT & CESDTOT \tabularnewline
anderen & 1 & 0.274 & 0.299 & 0.045 & 0.004 & -0.199 & 0.024 & 0.181 \tabularnewline
positief & 0.274 & 1 & 0.377 & 0.194 & -0.003 & -0.076 & -0.019 & 0.204 \tabularnewline
negatief & 0.299 & 0.377 & 1 & 0.148 & -0.108 & -0.166 & -0.122 & 0.298 \tabularnewline
organisatie & 0.045 & 0.194 & 0.148 & 1 & -0.082 & -0.082 & -0.05 & -0.009 \tabularnewline
CONFSTATTOT & 0.004 & -0.003 & -0.108 & -0.082 & 1 & 0.536 & 0.066 & -0.109 \tabularnewline
CONFSOFTTOT & -0.199 & -0.076 & -0.166 & -0.082 & 0.536 & 1 & 0.076 & -0.211 \tabularnewline
STRESSTOT & 0.024 & -0.019 & -0.122 & -0.05 & 0.066 & 0.076 & 1 & -0.126 \tabularnewline
CESDTOT & 0.181 & 0.204 & 0.298 & -0.009 & -0.109 & -0.211 & -0.126 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269662&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]anderen[/C][C]positief[/C][C]negatief[/C][C]organisatie[/C][C]CONFSTATTOT[/C][C]CONFSOFTTOT[/C][C]STRESSTOT[/C][C]CESDTOT[/C][/ROW]
[ROW][C]anderen[/C][C]1[/C][C]0.274[/C][C]0.299[/C][C]0.045[/C][C]0.004[/C][C]-0.199[/C][C]0.024[/C][C]0.181[/C][/ROW]
[ROW][C]positief[/C][C]0.274[/C][C]1[/C][C]0.377[/C][C]0.194[/C][C]-0.003[/C][C]-0.076[/C][C]-0.019[/C][C]0.204[/C][/ROW]
[ROW][C]negatief[/C][C]0.299[/C][C]0.377[/C][C]1[/C][C]0.148[/C][C]-0.108[/C][C]-0.166[/C][C]-0.122[/C][C]0.298[/C][/ROW]
[ROW][C]organisatie[/C][C]0.045[/C][C]0.194[/C][C]0.148[/C][C]1[/C][C]-0.082[/C][C]-0.082[/C][C]-0.05[/C][C]-0.009[/C][/ROW]
[ROW][C]CONFSTATTOT[/C][C]0.004[/C][C]-0.003[/C][C]-0.108[/C][C]-0.082[/C][C]1[/C][C]0.536[/C][C]0.066[/C][C]-0.109[/C][/ROW]
[ROW][C]CONFSOFTTOT[/C][C]-0.199[/C][C]-0.076[/C][C]-0.166[/C][C]-0.082[/C][C]0.536[/C][C]1[/C][C]0.076[/C][C]-0.211[/C][/ROW]
[ROW][C]STRESSTOT[/C][C]0.024[/C][C]-0.019[/C][C]-0.122[/C][C]-0.05[/C][C]0.066[/C][C]0.076[/C][C]1[/C][C]-0.126[/C][/ROW]
[ROW][C]CESDTOT[/C][C]0.181[/C][C]0.204[/C][C]0.298[/C][C]-0.009[/C][C]-0.109[/C][C]-0.211[/C][C]-0.126[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269662&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269662&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)
	anderen	positief	negatief	organisatie	CONFSTATTOT	CONFSOFTTOT	STRESSTOT	CESDTOT
anderen	1	0.274	0.299	0.045	0.004	-0.199	0.024	0.181
positief	0.274	1	0.377	0.194	-0.003	-0.076	-0.019	0.204
negatief	0.299	0.377	1	0.148	-0.108	-0.166	-0.122	0.298
organisatie	0.045	0.194	0.148	1	-0.082	-0.082	-0.05	-0.009
CONFSTATTOT	0.004	-0.003	-0.108	-0.082	1	0.536	0.066	-0.109
CONFSOFTTOT	-0.199	-0.076	-0.166	-0.082	0.536	1	0.076	-0.211
STRESSTOT	0.024	-0.019	-0.122	-0.05	0.066	0.076	1	-0.126
CESDTOT	0.181	0.204	0.298	-0.009	-0.109	-0.211	-0.126	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
anderen;positief	0.4345	0.3743	0.2736
p-value	(0)	(1e-04)	(0)
anderen;negatief	0.4713	0.4172	0.2994
p-value	(0)	(0)	(0)
anderen;organisatie	0.1066	0.0664	0.0454
p-value	(0.2656)	(0.4889)	(0.5072)
anderen;CONFSTATTOT	-0.0382	0.0034	0.0041
p-value	(0.695)	(0.9721)	(0.9528)
anderen;CONFSOFTTOT	-0.2316	-0.2731	-0.1986
p-value	(0.0159)	(0.0042)	(0.0051)
anderen;STRESSTOT	0.0556	0.0329	0.0244
p-value	(0.5673)	(0.7357)	(0.7328)
anderen;CESDTOT	0.2788	0.2475	0.1814
p-value	(0.0035)	(0.0098)	(0.0084)
positief;negatief	0.5315	0.5035	0.3773
p-value	(0)	(0)	(0)
positief;organisatie	0.1988	0.253	0.1935
p-value	(0.0365)	(0.0074)	(0.0052)
positief;CONFSTATTOT	-0.0206	-0.0039	-0.0029
p-value	(0.8322)	(0.9676)	(0.9678)
positief;CONFSOFTTOT	-0.1442	-0.1007	-0.0764
p-value	(0.1364)	(0.2997)	(0.2869)
positief;STRESSTOT	-0.001	-0.0291	-0.0191
p-value	(0.9915)	(0.765)	(0.7922)
positief;CESDTOT	0.2697	0.2862	0.2039
p-value	(0.0048)	(0.0027)	(0.0034)
negatief;organisatie	0.2507	0.2048	0.148
p-value	(0.008)	(0.0311)	(0.031)
negatief;CONFSTATTOT	-0.2061	-0.1498	-0.1075
p-value	(0.0323)	(0.1217)	(0.1247)
negatief;CONFSOFTTOT	-0.2603	-0.2378	-0.1664
p-value	(0.0065)	(0.0132)	(0.0189)
negatief;STRESSTOT	-0.114	-0.1683	-0.1224
p-value	(0.2401)	(0.0817)	(0.0873)
negatief;CESDTOT	0.4244	0.4008	0.298
p-value	(0)	(0)	(0)
organisatie;CONFSTATTOT	-0.1103	-0.1108	-0.0818
p-value	(0.2559)	(0.2535)	(0.2554)
organisatie;CONFSOFTTOT	-0.1232	-0.11	-0.0819
p-value	(0.204)	(0.257)	(0.2608)
organisatie;STRESSTOT	-0.0601	-0.0684	-0.0499
p-value	(0.5364)	(0.4818)	(0.4976)
organisatie;CESDTOT	0.0335	-0.0076	-0.0086
p-value	(0.7309)	(0.9378)	(0.9034)
CONFSTATTOT;CONFSOFTTOT	0.6358	0.6486	0.5363
p-value	(0)	(0)	(0)
CONFSTATTOT;STRESSTOT	0.0517	0.0876	0.066
p-value	(0.595)	(0.3672)	(0.3724)
CONFSTATTOT;CESDTOT	-0.1512	-0.1479	-0.1093
p-value	(0.1182)	(0.1266)	(0.1248)
CONFSOFTTOT;STRESSTOT	0.0907	0.0959	0.0765
p-value	(0.3505)	(0.3235)	(0.3075)
CONFSOFTTOT;CESDTOT	-0.3038	-0.2773	-0.2111
p-value	(0.0014)	(0.0037)	(0.0034)
STRESSTOT;CESDTOT	-0.147	-0.1632	-0.1258
p-value	(0.129)	(0.0916)	(0.0838)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
anderen;positief & 0.4345 & 0.3743 & 0.2736 \tabularnewline
p-value & (0) & (1e-04) & (0) \tabularnewline
anderen;negatief & 0.4713 & 0.4172 & 0.2994 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
anderen;organisatie & 0.1066 & 0.0664 & 0.0454 \tabularnewline
p-value & (0.2656) & (0.4889) & (0.5072) \tabularnewline
anderen;CONFSTATTOT & -0.0382 & 0.0034 & 0.0041 \tabularnewline
p-value & (0.695) & (0.9721) & (0.9528) \tabularnewline
anderen;CONFSOFTTOT & -0.2316 & -0.2731 & -0.1986 \tabularnewline
p-value & (0.0159) & (0.0042) & (0.0051) \tabularnewline
anderen;STRESSTOT & 0.0556 & 0.0329 & 0.0244 \tabularnewline
p-value & (0.5673) & (0.7357) & (0.7328) \tabularnewline
anderen;CESDTOT & 0.2788 & 0.2475 & 0.1814 \tabularnewline
p-value & (0.0035) & (0.0098) & (0.0084) \tabularnewline
positief;negatief & 0.5315 & 0.5035 & 0.3773 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
positief;organisatie & 0.1988 & 0.253 & 0.1935 \tabularnewline
p-value & (0.0365) & (0.0074) & (0.0052) \tabularnewline
positief;CONFSTATTOT & -0.0206 & -0.0039 & -0.0029 \tabularnewline
p-value & (0.8322) & (0.9676) & (0.9678) \tabularnewline
positief;CONFSOFTTOT & -0.1442 & -0.1007 & -0.0764 \tabularnewline
p-value & (0.1364) & (0.2997) & (0.2869) \tabularnewline
positief;STRESSTOT & -0.001 & -0.0291 & -0.0191 \tabularnewline
p-value & (0.9915) & (0.765) & (0.7922) \tabularnewline
positief;CESDTOT & 0.2697 & 0.2862 & 0.2039 \tabularnewline
p-value & (0.0048) & (0.0027) & (0.0034) \tabularnewline
negatief;organisatie & 0.2507 & 0.2048 & 0.148 \tabularnewline
p-value & (0.008) & (0.0311) & (0.031) \tabularnewline
negatief;CONFSTATTOT & -0.2061 & -0.1498 & -0.1075 \tabularnewline
p-value & (0.0323) & (0.1217) & (0.1247) \tabularnewline
negatief;CONFSOFTTOT & -0.2603 & -0.2378 & -0.1664 \tabularnewline
p-value & (0.0065) & (0.0132) & (0.0189) \tabularnewline
negatief;STRESSTOT & -0.114 & -0.1683 & -0.1224 \tabularnewline
p-value & (0.2401) & (0.0817) & (0.0873) \tabularnewline
negatief;CESDTOT & 0.4244 & 0.4008 & 0.298 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
organisatie;CONFSTATTOT & -0.1103 & -0.1108 & -0.0818 \tabularnewline
p-value & (0.2559) & (0.2535) & (0.2554) \tabularnewline
organisatie;CONFSOFTTOT & -0.1232 & -0.11 & -0.0819 \tabularnewline
p-value & (0.204) & (0.257) & (0.2608) \tabularnewline
organisatie;STRESSTOT & -0.0601 & -0.0684 & -0.0499 \tabularnewline
p-value & (0.5364) & (0.4818) & (0.4976) \tabularnewline
organisatie;CESDTOT & 0.0335 & -0.0076 & -0.0086 \tabularnewline
p-value & (0.7309) & (0.9378) & (0.9034) \tabularnewline
CONFSTATTOT;CONFSOFTTOT & 0.6358 & 0.6486 & 0.5363 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CONFSTATTOT;STRESSTOT & 0.0517 & 0.0876 & 0.066 \tabularnewline
p-value & (0.595) & (0.3672) & (0.3724) \tabularnewline
CONFSTATTOT;CESDTOT & -0.1512 & -0.1479 & -0.1093 \tabularnewline
p-value & (0.1182) & (0.1266) & (0.1248) \tabularnewline
CONFSOFTTOT;STRESSTOT & 0.0907 & 0.0959 & 0.0765 \tabularnewline
p-value & (0.3505) & (0.3235) & (0.3075) \tabularnewline
CONFSOFTTOT;CESDTOT & -0.3038 & -0.2773 & -0.2111 \tabularnewline
p-value & (0.0014) & (0.0037) & (0.0034) \tabularnewline
STRESSTOT;CESDTOT & -0.147 & -0.1632 & -0.1258 \tabularnewline
p-value & (0.129) & (0.0916) & (0.0838) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269662&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]anderen;positief[/C][C]0.4345[/C][C]0.3743[/C][C]0.2736[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](0)[/C][/ROW]
[ROW][C]anderen;negatief[/C][C]0.4713[/C][C]0.4172[/C][C]0.2994[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]anderen;organisatie[/C][C]0.1066[/C][C]0.0664[/C][C]0.0454[/C][/ROW]
[ROW][C]p-value[/C][C](0.2656)[/C][C](0.4889)[/C][C](0.5072)[/C][/ROW]
[ROW][C]anderen;CONFSTATTOT[/C][C]-0.0382[/C][C]0.0034[/C][C]0.0041[/C][/ROW]
[ROW][C]p-value[/C][C](0.695)[/C][C](0.9721)[/C][C](0.9528)[/C][/ROW]
[ROW][C]anderen;CONFSOFTTOT[/C][C]-0.2316[/C][C]-0.2731[/C][C]-0.1986[/C][/ROW]
[ROW][C]p-value[/C][C](0.0159)[/C][C](0.0042)[/C][C](0.0051)[/C][/ROW]
[ROW][C]anderen;STRESSTOT[/C][C]0.0556[/C][C]0.0329[/C][C]0.0244[/C][/ROW]
[ROW][C]p-value[/C][C](0.5673)[/C][C](0.7357)[/C][C](0.7328)[/C][/ROW]
[ROW][C]anderen;CESDTOT[/C][C]0.2788[/C][C]0.2475[/C][C]0.1814[/C][/ROW]
[ROW][C]p-value[/C][C](0.0035)[/C][C](0.0098)[/C][C](0.0084)[/C][/ROW]
[ROW][C]positief;negatief[/C][C]0.5315[/C][C]0.5035[/C][C]0.3773[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]positief;organisatie[/C][C]0.1988[/C][C]0.253[/C][C]0.1935[/C][/ROW]
[ROW][C]p-value[/C][C](0.0365)[/C][C](0.0074)[/C][C](0.0052)[/C][/ROW]
[ROW][C]positief;CONFSTATTOT[/C][C]-0.0206[/C][C]-0.0039[/C][C]-0.0029[/C][/ROW]
[ROW][C]p-value[/C][C](0.8322)[/C][C](0.9676)[/C][C](0.9678)[/C][/ROW]
[ROW][C]positief;CONFSOFTTOT[/C][C]-0.1442[/C][C]-0.1007[/C][C]-0.0764[/C][/ROW]
[ROW][C]p-value[/C][C](0.1364)[/C][C](0.2997)[/C][C](0.2869)[/C][/ROW]
[ROW][C]positief;STRESSTOT[/C][C]-0.001[/C][C]-0.0291[/C][C]-0.0191[/C][/ROW]
[ROW][C]p-value[/C][C](0.9915)[/C][C](0.765)[/C][C](0.7922)[/C][/ROW]
[ROW][C]positief;CESDTOT[/C][C]0.2697[/C][C]0.2862[/C][C]0.2039[/C][/ROW]
[ROW][C]p-value[/C][C](0.0048)[/C][C](0.0027)[/C][C](0.0034)[/C][/ROW]
[ROW][C]negatief;organisatie[/C][C]0.2507[/C][C]0.2048[/C][C]0.148[/C][/ROW]
[ROW][C]p-value[/C][C](0.008)[/C][C](0.0311)[/C][C](0.031)[/C][/ROW]
[ROW][C]negatief;CONFSTATTOT[/C][C]-0.2061[/C][C]-0.1498[/C][C]-0.1075[/C][/ROW]
[ROW][C]p-value[/C][C](0.0323)[/C][C](0.1217)[/C][C](0.1247)[/C][/ROW]
[ROW][C]negatief;CONFSOFTTOT[/C][C]-0.2603[/C][C]-0.2378[/C][C]-0.1664[/C][/ROW]
[ROW][C]p-value[/C][C](0.0065)[/C][C](0.0132)[/C][C](0.0189)[/C][/ROW]
[ROW][C]negatief;STRESSTOT[/C][C]-0.114[/C][C]-0.1683[/C][C]-0.1224[/C][/ROW]
[ROW][C]p-value[/C][C](0.2401)[/C][C](0.0817)[/C][C](0.0873)[/C][/ROW]
[ROW][C]negatief;CESDTOT[/C][C]0.4244[/C][C]0.4008[/C][C]0.298[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]organisatie;CONFSTATTOT[/C][C]-0.1103[/C][C]-0.1108[/C][C]-0.0818[/C][/ROW]
[ROW][C]p-value[/C][C](0.2559)[/C][C](0.2535)[/C][C](0.2554)[/C][/ROW]
[ROW][C]organisatie;CONFSOFTTOT[/C][C]-0.1232[/C][C]-0.11[/C][C]-0.0819[/C][/ROW]
[ROW][C]p-value[/C][C](0.204)[/C][C](0.257)[/C][C](0.2608)[/C][/ROW]
[ROW][C]organisatie;STRESSTOT[/C][C]-0.0601[/C][C]-0.0684[/C][C]-0.0499[/C][/ROW]
[ROW][C]p-value[/C][C](0.5364)[/C][C](0.4818)[/C][C](0.4976)[/C][/ROW]
[ROW][C]organisatie;CESDTOT[/C][C]0.0335[/C][C]-0.0076[/C][C]-0.0086[/C][/ROW]
[ROW][C]p-value[/C][C](0.7309)[/C][C](0.9378)[/C][C](0.9034)[/C][/ROW]
[ROW][C]CONFSTATTOT;CONFSOFTTOT[/C][C]0.6358[/C][C]0.6486[/C][C]0.5363[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CONFSTATTOT;STRESSTOT[/C][C]0.0517[/C][C]0.0876[/C][C]0.066[/C][/ROW]
[ROW][C]p-value[/C][C](0.595)[/C][C](0.3672)[/C][C](0.3724)[/C][/ROW]
[ROW][C]CONFSTATTOT;CESDTOT[/C][C]-0.1512[/C][C]-0.1479[/C][C]-0.1093[/C][/ROW]
[ROW][C]p-value[/C][C](0.1182)[/C][C](0.1266)[/C][C](0.1248)[/C][/ROW]
[ROW][C]CONFSOFTTOT;STRESSTOT[/C][C]0.0907[/C][C]0.0959[/C][C]0.0765[/C][/ROW]
[ROW][C]p-value[/C][C](0.3505)[/C][C](0.3235)[/C][C](0.3075)[/C][/ROW]
[ROW][C]CONFSOFTTOT;CESDTOT[/C][C]-0.3038[/C][C]-0.2773[/C][C]-0.2111[/C][/ROW]
[ROW][C]p-value[/C][C](0.0014)[/C][C](0.0037)[/C][C](0.0034)[/C][/ROW]
[ROW][C]STRESSTOT;CESDTOT[/C][C]-0.147[/C][C]-0.1632[/C][C]-0.1258[/C][/ROW]
[ROW][C]p-value[/C][C](0.129)[/C][C](0.0916)[/C][C](0.0838)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269662&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269662&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
pair	Pearson r	Spearman rho	Kendall tau
anderen;positief	0.4345	0.3743	0.2736
p-value	(0)	(1e-04)	(0)
anderen;negatief	0.4713	0.4172	0.2994
p-value	(0)	(0)	(0)
anderen;organisatie	0.1066	0.0664	0.0454
p-value	(0.2656)	(0.4889)	(0.5072)
anderen;CONFSTATTOT	-0.0382	0.0034	0.0041
p-value	(0.695)	(0.9721)	(0.9528)
anderen;CONFSOFTTOT	-0.2316	-0.2731	-0.1986
p-value	(0.0159)	(0.0042)	(0.0051)
anderen;STRESSTOT	0.0556	0.0329	0.0244
p-value	(0.5673)	(0.7357)	(0.7328)
anderen;CESDTOT	0.2788	0.2475	0.1814
p-value	(0.0035)	(0.0098)	(0.0084)
positief;negatief	0.5315	0.5035	0.3773
p-value	(0)	(0)	(0)
positief;organisatie	0.1988	0.253	0.1935
p-value	(0.0365)	(0.0074)	(0.0052)
positief;CONFSTATTOT	-0.0206	-0.0039	-0.0029
p-value	(0.8322)	(0.9676)	(0.9678)
positief;CONFSOFTTOT	-0.1442	-0.1007	-0.0764
p-value	(0.1364)	(0.2997)	(0.2869)
positief;STRESSTOT	-0.001	-0.0291	-0.0191
p-value	(0.9915)	(0.765)	(0.7922)
positief;CESDTOT	0.2697	0.2862	0.2039
p-value	(0.0048)	(0.0027)	(0.0034)
negatief;organisatie	0.2507	0.2048	0.148
p-value	(0.008)	(0.0311)	(0.031)
negatief;CONFSTATTOT	-0.2061	-0.1498	-0.1075
p-value	(0.0323)	(0.1217)	(0.1247)
negatief;CONFSOFTTOT	-0.2603	-0.2378	-0.1664
p-value	(0.0065)	(0.0132)	(0.0189)
negatief;STRESSTOT	-0.114	-0.1683	-0.1224
p-value	(0.2401)	(0.0817)	(0.0873)
negatief;CESDTOT	0.4244	0.4008	0.298
p-value	(0)	(0)	(0)
organisatie;CONFSTATTOT	-0.1103	-0.1108	-0.0818
p-value	(0.2559)	(0.2535)	(0.2554)
organisatie;CONFSOFTTOT	-0.1232	-0.11	-0.0819
p-value	(0.204)	(0.257)	(0.2608)
organisatie;STRESSTOT	-0.0601	-0.0684	-0.0499
p-value	(0.5364)	(0.4818)	(0.4976)
organisatie;CESDTOT	0.0335	-0.0076	-0.0086
p-value	(0.7309)	(0.9378)	(0.9034)
CONFSTATTOT;CONFSOFTTOT	0.6358	0.6486	0.5363
p-value	(0)	(0)	(0)
CONFSTATTOT;STRESSTOT	0.0517	0.0876	0.066
p-value	(0.595)	(0.3672)	(0.3724)
CONFSTATTOT;CESDTOT	-0.1512	-0.1479	-0.1093
p-value	(0.1182)	(0.1266)	(0.1248)
CONFSOFTTOT;STRESSTOT	0.0907	0.0959	0.0765
p-value	(0.3505)	(0.3235)	(0.3075)
CONFSOFTTOT;CESDTOT	-0.3038	-0.2773	-0.2111
p-value	(0.0014)	(0.0037)	(0.0034)
STRESSTOT;CESDTOT	-0.147	-0.1632	-0.1258
p-value	(0.129)	(0.0916)	(0.0838)

Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I error	Pearson r	Spearman rho	Kendall tau
0.01	0.36	0.36	0.36
0.02	0.39	0.39	0.39
0.03	0.39	0.39	0.39
0.04	0.46	0.43	0.43
0.05	0.46	0.43	0.43
0.06	0.46	0.43	0.43
0.07	0.46	0.43	0.43
0.08	0.46	0.43	0.43
0.09	0.46	0.46	0.5
0.1	0.46	0.5	0.5

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Correlation Tests \tabularnewline
Number of significant by total number of Correlations \tabularnewline
Type I error & Pearson r & Spearman rho & Kendall tau \tabularnewline
0.01 & 0.36 & 0.36 & 0.36 \tabularnewline
0.02 & 0.39 & 0.39 & 0.39 \tabularnewline
0.03 & 0.39 & 0.39 & 0.39 \tabularnewline
0.04 & 0.46 & 0.43 & 0.43 \tabularnewline
0.05 & 0.46 & 0.43 & 0.43 \tabularnewline
0.06 & 0.46 & 0.43 & 0.43 \tabularnewline
0.07 & 0.46 & 0.43 & 0.43 \tabularnewline
0.08 & 0.46 & 0.43 & 0.43 \tabularnewline
0.09 & 0.46 & 0.46 & 0.5 \tabularnewline
0.1 & 0.46 & 0.5 & 0.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269662&T=3

[TABLE]
[ROW][C]Meta Analysis of Correlation Tests[/C][/ROW]
[ROW][C]Number of significant by total number of Correlations[/C][/ROW]
[ROW][C]Type I error[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]0.01[/C][C]0.36[/C][C]0.36[/C][C]0.36[/C][/ROW]
[ROW][C]0.02[/C][C]0.39[/C][C]0.39[/C][C]0.39[/C][/ROW]
[ROW][C]0.03[/C][C]0.39[/C][C]0.39[/C][C]0.39[/C][/ROW]
[ROW][C]0.04[/C][C]0.46[/C][C]0.43[/C][C]0.43[/C][/ROW]
[ROW][C]0.05[/C][C]0.46[/C][C]0.43[/C][C]0.43[/C][/ROW]
[ROW][C]0.06[/C][C]0.46[/C][C]0.43[/C][C]0.43[/C][/ROW]
[ROW][C]0.07[/C][C]0.46[/C][C]0.43[/C][C]0.43[/C][/ROW]
[ROW][C]0.08[/C][C]0.46[/C][C]0.43[/C][C]0.43[/C][/ROW]
[ROW][C]0.09[/C][C]0.46[/C][C]0.46[/C][C]0.5[/C][/ROW]
[ROW][C]0.1[/C][C]0.46[/C][C]0.5[/C][C]0.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269662&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269662&T=3

As an alternative you can also use a QR Code:

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

Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I error	Pearson r	Spearman rho	Kendall tau
0.01	0.36	0.36	0.36
0.02	0.39	0.39	0.39
0.03	0.39	0.39	0.39
0.04	0.46	0.43	0.43
0.05	0.46	0.43	0.43
0.06	0.46	0.43	0.43
0.07	0.46	0.43	0.43
0.08	0.46	0.43	0.43
0.09	0.46	0.46	0.5
0.1	0.46	0.5	0.5

Figure 1

PNG link

Postscript link

PDF link

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')
ncorrs <- (n*n -n)/2
mycorrs <- array(0, dim=c(10,3))
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)
for (iii in 1:10) {
iiid100 <- iii / 100
if (rp$p.value < iiid100) mycorrs[iii, 1] = mycorrs[iii, 1] + 1
if (rs$p.value < iiid100) mycorrs[iii, 2] = mycorrs[iii, 2] + 1
if (rk$p.value < iiid100) mycorrs[iii, 3] = mycorrs[iii, 3] + 1
}
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Correlation Tests',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of significant by total number of Correlations',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Type I error',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)
for (iii in 1:10) {
iiid100 <- iii / 100
a<-table.row.start(a)
a<-table.element(a,round(iiid100,2),header=T)
a<-table.element(a,round(mycorrs[iii,1]/ncorrs,2))
a<-table.element(a,round(mycorrs[iii,2]/ncorrs,2))
a<-table.element(a,round(mycorrs[iii,3]/ncorrs,2))
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