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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_chi_squared_tests.wasp

Title produced by software

Chi-Squared and McNemar Tests

Date of computation

Thu, 11 Nov 2010 12:02:03 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/11/t12894768416uvrck0hamuprsb.htm/, Retrieved Thu, 25 Apr 2024 07:05:18 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=93210, Retrieved Thu, 25 Apr 2024 07:05:18 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

189

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [ECEL 2008] [ECEL2008 hypothes...] [2008-06-14 21:17:24] [74be16979710d4c4e7c6647856088456]
F RMPD    [Chi-Squared and McNemar Tests] [Separate versus H...] [2010-11-11 12:02:03] [b6992a7b26e556359948e164e4227eba] [Current]

Feedback Forum

2010-11-23 18:31:31 [411b43619fc9db329bbcdbf7261c55fb] [reply] 
Hier zien we dat de cell count te laag is (sommige waarden lager dan 5), daarom gebruiken we de “Exact Pearson Chi-squared by simulation” (de student gebruikt deze niet). Bekijk http://www.freestatistics.org/blog/index.php?v=date/2010/Nov/20/t1290249701wxdndkd58pu5t4s.htm/ voor A/B/C/D. De student gaf aan bij zijn conclusie dat er hier geen verband was, dit is niet correct. Als we hier kijken naar de p-waarde (tabel “Statistical Results”) dan zien we dat deze hoger is dan de vooropgestelde type 1 fout (5%), namelijk 6% (het is voor discussie vatbaar of het al dan niet significant verschillend is, gezien de lage P-waarde). Bijgevolg is er hier een mogelijk verband tussen de reële en verwachte waarde. Als we vervolgens naar de grafiek kijken, dan zien we 1 significant verschil bij C-C (donker grijs gekleurd positief balkje). Toch kunnen we hier nog twijfelen over het verband. Opmerking: doordat de student niet de juiste test heeft gebruikt, merk ik op dat hij een andere p-waarde uitkomt. 
 
Aangezien de cell count (zoals eerder aangehaald) niet OK is, gaan we ook nog even de vergelijking making op basis van de groffe indeling HI/LO. (bekijk http://www.freestatistics.org/blog/index.php?v=date/2010/Nov/20/t1290248317hdutnii5c00439w.htm/ berekening met “Pearson Chi-squared test”) Als we hier kijken naar de p-waarde (tabel “Statiscal Results”) dan zien we dat deze hier lager ligt dan de vooropgestelde type 1 fout (5%), namelijk 2%. Hier kunnen we met meer zekerheid zeggen dat er een verband is. Wel is het verschil hier niet significant (dit zien we duidelijk op de grafiek), want er is geen balkje dat gekleurd (rood of blauw) is. Verder zien we deze blokjes op de hoofddiagonaal (van linksboven naar rechtsonder) boven de stippellijn (de reële frequentie ligt hoger dan de verwachte frequentie) liggen. En op de andere diagonaal (van linksonder naar rechtsboven) onder de stippellijn liggen. Dit wijst bijgevolg op een positief verband. 
 
De conclusie hier is dus dat seperate learners happier zijn. Maar deze berekening zegt niets over oorzaak en gevolg. Bij deze beoordeling hangt er niet vanaf of je de Chi-squared test gebruikt, maar wel hoe je de gegevens bekomen bent. Het gaat hier over een experiment, niet gerandomiseerd, … We kunnen dus eigenlijk niet zeggen dat seperate learning u een gelukkig gevoel geeft. 

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'A'	'C'	'A'	'C'
'D'	'B'	'D'	'A'
'D'	'C'	'D'	'B'
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'B'	'C'	'D'	'A'
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'C'	'B'	'B'	'C'
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'B'	'A'	'D'	'A'
'C'	'C'	'D'	'C'
'A'	'C'	'B'	'B'
'A'	'B'	'A'	'B'
'D'	'B'	'B'	'D'
'A'	'B'	'D'	'D'
'B'	'B'	'D'	'A'
'D'	'D'	'D'	'A'
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'B'	'A'	'B'	'A'
'A'	'B'	'B'	'B'
'D'	'A'	'A'	'A'
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'C'	'B'	'B'	'C'
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'C'	'D'	'B'	'B'
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'C'	'B'	'B'	'B'
'D'	'C'	'C'	'A'
'C'	'C'	'D'	'A'
'D'	'B'	'A'	'B'
'B'	'C'	'C'	'A'
'B'	'A'	'B'	'B'
'C'	'D'	'B'	'A'
'D'	'D'	'C'	'D'
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'A'	'B'	'D'	'A'
'B'	'D'	'B'	'C'
'A'	'B'	'A'	'C'
'C'	'B'	'B'	'D'
'A'	'B'	'A'	'D'
'A'	'B'	'D'	'A'
'B'	'A'	'A'	'B'
'C'	'D'	'D'	'C'
'C'	'A'	'B'	'A'
'A'	'C'	'D'	'A'
'A'	'B'	'A'	'C'
'A'	'A'	'B'	'A'
'B'	'B'	'D'	'A'
'A'	'A'	'D'	'A'
'D'	'B'	'B'	'A'
'D'	'C'	'D'	'A'
'C'	'A'	'C'	'C'
'C'	'C'	'B'	'A'
'A'	'B'	'A'	'B'
'A'	'C'	'A'	'D'
'C'	'A'	'B'	'A'
'B'	'A'	'B'	'B'
'C'	'B'	'B'	'D'
'A'	'B'	'B'	'A'
'C'	'A'	'D'	'A'
'D'	'D'	'B'	'A'
'A'	'A'	'B'	'C'
'A'	'A'	'B'	'D'
'C'	'D'	'B'	'C'
'D'	'C'	'C'	'C'
'A'	'C'	'A'	'D'
'A'	'A'	'A'	'D'
'C'	'B'	'A'	'C'
'B'	'C'	'B'	'B'
'C'	'C'	'C'	'C'
'D'	'C'	'D'	'A'
'A'	'A'	'B'	'D'
'D'	'D'	'B'	'A'
'A'	'A'	'B'	'B'
'C'	'D'	'A'	'A'
'D'	'D'	'D'	'A'
'B'	'B'	'B'	'A'
'D'	'B'	'D'	'A'
'B'	'B'	'B'	'C'
'D'	'B'	'C'	'B'
'C'	'B'	'B'	'D'
'D'	'B'	'A'	'A'
'D'	'B'	'B'	'B'
'D'	'D'	'B'	'B'
'A'	'D'	'A'	'C'
'C'	'D'	'A'	'B'
'B'	'B'	'D'	'B'
'C'	'D'	'D'	'C'
'B'	'C'	'D'	'A'
'A'	'A'	'A'	'B'
'A'	'A'	'C'	'A'
'B'	'A'	'A'	'D'
'B'	'A'	'D'	'B'
'B'	'B'	'D'	'A'
'C'	'D'	'C'	'A'
'B'	'C'	'C'	'A'
'C'	'A'	'B'	'A'
'C'	'B'	'A'	'C'
'B'	'C'	'C'	'D'
'C'	'B'	'D'	'A'
'B'	'B'	'C'	'A'

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	9 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\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 & 9 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=93210&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=93210&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=93210&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	9 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Tabulation of Results
Separate x Happiness
	A	B	C	D
A	13	23	2	6
B	12	17	3	14
C	10	8	9	11
D	8	12	5	9

\begin{tabular}{lllllllll}
\hline
Tabulation of Results \tabularnewline
Separate  x  Happiness \tabularnewline
  & A & B & C & D \tabularnewline
A & 13 & 23 & 2 & 6 \tabularnewline
B & 12 & 17 & 3 & 14 \tabularnewline
C & 10 & 8 & 9 & 11 \tabularnewline
D & 8 & 12 & 5 & 9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=93210&T=1

[TABLE]
[ROW][C]Tabulation of Results[/C][/ROW]
[ROW][C]Separate  x  Happiness[/C][/ROW]
[ROW][C] [/C][C]A[/C][C]B[/C][C]C[/C][C]D[/C][/ROW]
[C]A[/C][C]13[/C][C]23[/C][C]2[/C][C]6[/C][/ROW]
[C]B[/C][C]12[/C][C]17[/C][C]3[/C][C]14[/C][/ROW]
[C]C[/C][C]10[/C][C]8[/C][C]9[/C][C]11[/C][/ROW]
[C]D[/C][C]8[/C][C]12[/C][C]5[/C][C]9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=93210&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=93210&T=1

As an alternative you can also use a QR Code:

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

Tabulation of Results
Separate x Happiness
	A	B	C	D
A	13	23	2	6
B	12	17	3	14
C	10	8	9	11
D	8	12	5	9

Tabulation of Expected Results
Separate x Happiness
	A	B	C	D
A	11.68	16.3	5.16	10.86
B	12.21	17.04	5.4	11.36
C	10.09	14.07	4.46	9.38
D	9.02	12.59	3.99	8.4

\begin{tabular}{lllllllll}
\hline
Tabulation of Expected Results \tabularnewline
Separate  x  Happiness \tabularnewline
  & A & B & C & D \tabularnewline
A & 11.68 & 16.3 & 5.16 & 10.86 \tabularnewline
B & 12.21 & 17.04 & 5.4 & 11.36 \tabularnewline
C & 10.09 & 14.07 & 4.46 & 9.38 \tabularnewline
D & 9.02 & 12.59 & 3.99 & 8.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=93210&T=2

[TABLE]
[ROW][C]Tabulation of Expected Results[/C][/ROW]
[ROW][C]Separate  x  Happiness[/C][/ROW]
[ROW][C] [/C][C]A[/C][C]B[/C][C]C[/C][C]D[/C][/ROW]
[C]A[/C][C]11.68[/C][C]16.3[/C][C]5.16[/C][C]10.86[/C][/ROW]
[C]B[/C][C]12.21[/C][C]17.04[/C][C]5.4[/C][C]11.36[/C][/ROW]
[C]C[/C][C]10.09[/C][C]14.07[/C][C]4.46[/C][C]9.38[/C][/ROW]
[C]D[/C][C]9.02[/C][C]12.59[/C][C]3.99[/C][C]8.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=93210&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=93210&T=2

As an alternative you can also use a QR Code:

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

Tabulation of Expected Results
Separate x Happiness
	A	B	C	D
A	11.68	16.3	5.16	10.86
B	12.21	17.04	5.4	11.36
C	10.09	14.07	4.46	9.38
D	9.02	12.59	3.99	8.4

Statistical Results
Pearson's Chi-squared test
Chi Square Statistic	16.68
Degrees of Freedom	9
P value	0.05

\begin{tabular}{lllllllll}
\hline
Statistical Results \tabularnewline
Pearson's Chi-squared test \tabularnewline
Chi Square Statistic & 16.68 \tabularnewline
Degrees of Freedom & 9 \tabularnewline
P value & 0.05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=93210&T=3

[TABLE]
[ROW][C]Statistical Results[/C][/ROW]
[ROW][C]Pearson's Chi-squared test[/C][/ROW]
[ROW][C]Chi Square Statistic[/C][C]16.68[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]9[/C][/ROW]
[ROW][C]P value[/C][C]0.05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=93210&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=93210&T=3

As an alternative you can also use a QR Code:

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

Statistical Results
Pearson's Chi-squared test
Chi Square Statistic	16.68
Degrees of Freedom	9
P value	0.05

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 2 ; par2 = 3 ; par3 = Pearson Chi-Squared ;

Parameters (R input):

par1 = 2 ; par2 = 3 ; par3 = Pearson Chi-Squared ;

R code (references can be found in the software module):

library(vcd)
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
simulate.p.value=FALSE
if (par3 == 'Exact Pearson Chi-Squared by Simulation') simulate.p.value=TRUE
x <- t(x)
(z <- array(unlist(x),dim=c(length(x[,1]),length(x[1,]))))
(table1 <- table(z[,cat1],z[,cat2]))
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
bitmap(file='pic1.png')
assoc(ftable(z[,cat1],z[,cat2],row.vars=1,dnn=c(V1,V2)),shade=T)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tabulation of Results',ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1,TRUE)
for(nc in 1:ncol(table1)){
a<-table.element(a, colnames(table1)[nc], 1, TRUE)
}
a<-table.row.end(a)
for(nr in 1:nrow(table1) ){
a<-table.element(a, rownames(table1)[nr], 1, TRUE)
for(nc in 1:ncol(table1) ){
a<-table.element(a, table1[nr, nc], 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
(cst<-chisq.test(table1, simulate.p.value=simulate.p.value) )
if (par3 == 'McNemar Chi-Squared') {
(cst <- mcnemar.test(table1))
}
if (par3 != 'McNemar Chi-Squared') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tabulation of Expected Results',ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1,TRUE)
for(nc in 1:ncol(table1)){
a<-table.element(a, colnames(table1)[nc], 1, TRUE)
}
a<-table.row.end(a)
for(nr in 1:nrow(table1) ){
a<-table.element(a, rownames(table1)[nr], 1, TRUE)
for(nc in 1:ncol(table1) ){
a<-table.element(a, round(cst$expected[nr, nc], digits=2), 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
}
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Statistical Results',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, cst$method, 2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Chi Square Statistic', 1, TRUE)
a<-table.element(a, round(cst$statistic, digits=2), 1,FALSE)
a<-table.row.end(a)
if(!simulate.p.value){
a<-table.row.start(a)
a<-table.element(a, 'Degrees of Freedom', 1, TRUE)
a<-table.element(a, cst$parameter, 1,FALSE)
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'P value', 1, TRUE)
a<-table.element(a, round(cst$p.value, digits=2), 1,FALSE)
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