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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_partialcorrelation.wasp
Title produced by softwarePartial Correlation
Date of computationTue, 11 Nov 2008 09:11:52 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/11/t1226419960a0nrmt0tokkeei0.htm/, Retrieved Sun, 19 May 2024 10:56:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23644, Retrieved Sun, 19 May 2024 10:56:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Partial Correlation] [Partial correlation] [2008-11-04 19:15:33] [077ffec662d24c06be4c491541a44245]
F   P     [Partial Correlation] [Partial correlation] [2008-11-11 16:11:52] [e81ac192d6ae6d77191d83851a692999] [Current]
F   P       [Partial Correlation] [Partial Correlation] [2008-11-11 17:31:20] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
F             [Partial Correlation] [] [2008-11-11 19:37:29] [a7a7b7de998247cdf0f65ef79d563d66]
F RMP         [Trivariate Scatterplots] [] [2008-11-11 19:40:32] [a7a7b7de998247cdf0f65ef79d563d66]
-             [Partial Correlation] [] [2008-11-21 17:12:08] [888addc516c3b812dd7be4bd54caa358]
Feedback Forum
2008-11-18 13:25:02 [Gregory Van Overmeiren] [reply] 
We gaan hier 3 variabelen met elkaar vergelijken (x,y en z).

Correlation r(xy) 0.902863979754093
Partial Correlation r(xy.z) 0.283888723977228

Hier zien we een correlatie van 0.90 tussen X en Y.

Als we de partiële correlatie bekijken r(X,Y|Z) (=> De variabele rechts van de verticale lijn is de “control variable”.) zien we dat de correlatie gezakt is van 0.90 naar 0.28! Met andere woorden, r(X,Y|Z) is een berekening van de relatie tussen X en Y, als we Z constant houden. Dus als r(X,Y) relatief groot is, zoals hier het geval is, maar r(X,Y|Z) veel kleiner is, kunnen we besluiten dat Z een tussenkomende variabele is (=> mediating variable).

Ook bij de relatie tussen Y en Z is X een mediating variable.

2008-11-24 18:32:47 [Bart Haemels] [reply] 
Er is hier gebruik gemaakt van de methode van Partial Correlation. Bij deze methode redeneert als volgt. Een tijdreeks z kan een positief verband hebben met tijdreeks x en een negatief verband vertonen met tijdreeks y. Als z zou stijgen, houdt dit in dat x mee zou stijgen (positieve correlatie) en y zou dalen (negatieve correlatie). Hieruit zou dan besloten kunnen worden dat tijdreeksen x en y onderling een negatief verband zouden hebben. Dit is niet volledig correct aangezien dit 'verband' beinvloedt wordt door tijdreeks z. Door deze methode te gebruiken, wordt dit vermeden. Zo wordt in deze tabel de eerste partial correlation berekend tussen x en y waarbij de invloed van z wordt weggefilterd (want het beeld zou door z vertekend kunnen worden).

In deze tabel kunnen we zien dat de 'gewone' correlatie tussen x en y 0,90bedraagt maar als de partiele correlatie berekend wordt tussen x en y waarbij de invloed van z weggefilterd wordt, bekomen we een correlatiewaarde van 0,28. Dit is dus echt een groot verschil.
Dit houdt in dat de invloed van z toch vrij groot is op x en y.
2008-12-19 22:43:36 [Gregory Van Overmeiren] [reply] 
@ Bart : Mooie copy/paste van de feedback die je zelf hebt gekregen van Kevin Neelen...
2008-12-19 22:46:58 [Bonifer Spillemaeckers] [reply] 
Wat een plagiaat!!! Zo geraak ik ook aan mijn punten !!!
2008-12-19 22:47:59 [Jan Van Riet] [reply] 
Schande Schande !!!

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12300.00
12092.80
12380.80
12196.90
9455.00
13168.00
13427.90
11980.50
11884.80
11691.70
12233.80
14341.40
13130.70
12421.10
14285.80
12864.60
11160.20
14316.20
14388.70
14013.90
13419.00
12769.60
13315.50
15332.90
14243.00
13824.40
14962.90
13202.90
12199.00
15508.90
14199.80
15169.60
14058.00
13786.20
14147.90
16541.70
13587.50
15582.40
15802.80
14130.50
12923.20
15612.20
16033.70
16036.60
14037.80
15330.60
15038.30
17401.80
14992.50
16043.70
16929.60
15921.30
14417.20
15961.00
17851.90
16483.90
14215.50
17429.70
17839.50
17629.20
Dataseries Y:
Download CSV
Histogram 
3423.40
3242.80
3277.20
3833.00
2606.30
3643.80
3686.40
3281.60
3669.30
3191.50
3512.70
3970.70
3601.20
3610.00
4172.10
3956.20
3142.70
3884.30
3892.20
3613.00
3730.50
3481.30
3649.50
4215.20
4066.60
4196.80
4536.60
4441.60
3548.30
4735.90
4130.60
4356.20
4159.60
3988.00
4167.80
4902.20
3909.40
4697.60
4308.90
4420.40
3544.20
4433.00
4479.70
4533.20
4237.50
4207.40
4394.00
5148.40
4202.20
4682.50
4884.30
5288.90
4505.20
4611.50
5081.10
4523.10
4412.80
4647.40
4778.60
4495.30
Dataseries Z:
Download CSV
Histogram 
15370.60
14956.90
15469.70
15101.80
11703.70
16283.60
16726.50
14968.90
14861.00
14583.30
15305.80
17903.90
16379.40
15420.30
17870.50
15912.80
13866.50
17823.20
17872.00
17420.40
16704.40
15991.20
16583.60
19123.50
17838.70
17209.40
18586.50
16258.10
15141.60
19202.10
17746.50
19090.10
18040.30
17515.50
17751.80
21072.40
17170.00
19439.50
19795.40
17574.90
16165.40
19464.60
19932.10
19961.20
17343.40
18924.20
18574.10
21350.60
18594.60
19823.10
20844.40
19640.20
17735.40
19813.60
22238.50
20682.20
17818.60
21872.10
22117.00
21865.90

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23644&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23644&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23644&T=0

As an alternative you can also use a QR Code:  
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 time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Pearson Product Moment Partial Correlation - Ungrouped Data
StatisticValue
Correlation r(xy)0.902863979754093
Partial Correlation r(xy.z)0.283888723977228
Correlation r(xz)0.997734994643543
Partial Correlation r(xz.y)0.988682211673432
Correlation r(yz)0.89643119900075
Partial Correlation r(yz.x)-0.151721858663955

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Partial Correlation - Ungrouped Data \tabularnewline
Statistic & Value \tabularnewline
Correlation r(xy) & 0.902863979754093 \tabularnewline
Partial Correlation r(xy.z) & 0.283888723977228 \tabularnewline
Correlation r(xz) & 0.997734994643543 \tabularnewline
Partial Correlation r(xz.y) & 0.988682211673432 \tabularnewline
Correlation r(yz) & 0.89643119900075 \tabularnewline
Partial Correlation r(yz.x) & -0.151721858663955 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23644&T=1

[TABLE]
[ROW][C]Pearson Product Moment Partial Correlation - Ungrouped Data[/C][/ROW]
[ROW][C]Statistic[/C][C]Value[/C][/ROW]
[ROW][C]Correlation r(xy)[/C][C]0.902863979754093[/C][/ROW]
[ROW][C]Partial Correlation r(xy.z)[/C][C]0.283888723977228[/C][/ROW]
[ROW][C]Correlation r(xz)[/C][C]0.997734994643543[/C][/ROW]
[ROW][C]Partial Correlation r(xz.y)[/C][C]0.988682211673432[/C][/ROW]
[ROW][C]Correlation r(yz)[/C][C]0.89643119900075[/C][/ROW]
[ROW][C]Partial Correlation r(yz.x)[/C][C]-0.151721858663955[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23644&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23644&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Pearson Product Moment Partial Correlation - Ungrouped Data
StatisticValue
Correlation r(xy)0.902863979754093
Partial Correlation r(xy.z)0.283888723977228
Correlation r(xz)0.997734994643543
Partial Correlation r(xz.y)0.988682211673432
Correlation r(yz)0.89643119900075
Partial Correlation r(yz.x)-0.151721858663955


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = uitvoer Vlaanderen ; par6 = uitvoer Belgie naar landen buiten EU ; par7 = uitvoer Belgie (totaal) ;
Parameters (R input):
R code (references can be found in the software module):
(rho12 <- cor(x, y))
(rho23 <- cor(y, z))
(rho13 <- cor(x, z))
(rhoxy_z <- (rho12-(rho13*rho23))/(sqrt(1-(rho13*rho13)) * sqrt(1-(rho23*rho23))))
(rhoxz_y <- (rho13-(rho12*rho23))/(sqrt(1-(rho12*rho12)) * sqrt(1-(rho23*rho23))))
(rhoyz_x <- (rho23-(rho12*rho13))/(sqrt(1-(rho12*rho12)) * sqrt(1-(rho13*rho13))))
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson Product Moment Partial Correlation - Ungrouped Data',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Statistic',1,TRUE)
a<-table.element(a,'Value',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation r(xy)',header=TRUE)
a<-table.element(a,rho12)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('partial_correlation1.htm','Partial Correlation r(xy.z)',''),header=TRUE)
a<-table.element(a,rhoxy_z)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation r(xz)',header=TRUE)
a<-table.element(a,rho13)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('partial_correlation1.htm','Partial Correlation r(xz.y)',''),header=TRUE)
a<-table.element(a,rhoxz_y)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation r(yz)',header=TRUE)
a<-table.element(a,rho23)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('partial_correlation1.htm','Partial Correlation r(yz.x)',''),header=TRUE)
a<-table.element(a,rhoyz_x)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')