Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

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

Mon, 15 Nov 2010 13:46:28 +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/15/t1289829161srumod3nhee6gh3.htm/, Retrieved Sun, 28 Apr 2024 10:26:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=94831, Retrieved Sun, 28 Apr 2024 10:26:44 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

206

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

F       [Chi-Squared and McNemar Tests] [] [2010-11-15 13:46:28] [6c31f786e793d35ef3a03978bc5de774] [Current]
F    D    [Chi-Squared and McNemar Tests] [] [2010-11-15 13:59:06] [dd4fe494cff2ee46c12b15bdc7b848ca] 
F    D      [Chi-Squared and McNemar Tests] [] [2010-11-15 14:07:39] [dd4fe494cff2ee46c12b15bdc7b848ca] 
F    D        [Chi-Squared and McNemar Tests] [] [2010-11-15 14:10:29] [dd4fe494cff2ee46c12b15bdc7b848ca] 

Feedback Forum

2010-11-20 08:45:25 [] [reply] 
Algemene opmerking: Als je de Chi-squared test uitvoert is er blijkbaar een bijkomende voorwaarde, namelijk de minimum cell count moet gelijk zijn aan 5. In de berekening zie je in de tabel van de berekeningen of er al dan niet lage cell-counts zijn. Indien er lage cell-counts zijn, moet je een speciale type van Chi-squared test gebruiken, namelijk deze met een gesimuleerde p-value. Dit is een simulatietechniek die ook toepasbaar is voor lage cell-counts 
2010-11-20 08:45:43 [] [reply] 
Hier gebruiken we de Chi-Squared test met gesimuleerde p-value. En de p-value is hier 0.19. Deze p-value is te hoog om over een verband te mogen spreken. Dus er is geen verband. Er is geen verschil tussen de verwachte en geobserveerde frequenties. In de grafiek zie je wel dat studenten met hoge connected attitude ook hogere happiness vertonen. Maar dit kan door toeval zijn, door trekking steekproef.
2010-11-20 15:24:23 [48eb36e2c01435ad7e4ea7854a9d98fe] [reply] 
Zoals door de student hierboven reeds werd besproken dient men, wanneer de celcount lager is dan 5, gebruik te maken van de zogenaamde 'Pearson's chi squared test with simulates P value'. Een voorbeeld daarvan is hier terug te vinden: http://www.freestatistics.org/blog/date/2010/Nov/16/t1289918170122lbf5d851og14.htm/ 
 
Een andere mogelijkheid is om maar te werken met 2 reeksen, namelijk high en low. Dan is de cel count wel voldoende: http://www.freestatistics.org/blog/date/2010/Nov/16/t128992067214cka5nztborve0.htm/ 
 
De interpretatie van de P waarde werd hierboven reeds beschreven.

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94831&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94831&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94831&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	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Tabulation of Results
Connected x Happiness
	A	B	C	D
A	21	18	4	11
B	8	16	7	12
C	9	18	3	7
D	5	8	5	10

\begin{tabular}{lllllllll}
\hline
Tabulation of Results \tabularnewline
Connected  x  Happiness \tabularnewline
  & A & B & C & D \tabularnewline
A & 21 & 18 & 4 & 11 \tabularnewline
B & 8 & 16 & 7 & 12 \tabularnewline
C & 9 & 18 & 3 & 7 \tabularnewline
D & 5 & 8 & 5 & 10 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94831&T=1

[TABLE]
[ROW][C]Tabulation of Results[/C][/ROW]
[ROW][C]Connected  x  Happiness[/C][/ROW]
[ROW][C] [/C][C]A[/C][C]B[/C][C]C[/C][C]D[/C][/ROW]
[C]A[/C][C]21[/C][C]18[/C][C]4[/C][C]11[/C][/ROW]
[C]B[/C][C]8[/C][C]16[/C][C]7[/C][C]12[/C][/ROW]
[C]C[/C][C]9[/C][C]18[/C][C]3[/C][C]7[/C][/ROW]
[C]D[/C][C]5[/C][C]8[/C][C]5[/C][C]10[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94831&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94831&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
Connected x Happiness
	A	B	C	D
A	21	18	4	11
B	8	16	7	12
C	9	18	3	7
D	5	8	5	10

Tabulation of Expected Results
Connected x Happiness
	A	B	C	D
A	14.33	20	6.33	13.33
B	11.41	15.93	5.04	10.62
C	9.82	13.7	4.34	9.14
D	7.43	10.37	3.28	6.91

\begin{tabular}{lllllllll}
\hline
Tabulation of Expected Results \tabularnewline
Connected  x  Happiness \tabularnewline
  & A & B & C & D \tabularnewline
A & 14.33 & 20 & 6.33 & 13.33 \tabularnewline
B & 11.41 & 15.93 & 5.04 & 10.62 \tabularnewline
C & 9.82 & 13.7 & 4.34 & 9.14 \tabularnewline
D & 7.43 & 10.37 & 3.28 & 6.91 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94831&T=2

[TABLE]
[ROW][C]Tabulation of Expected Results[/C][/ROW]
[ROW][C]Connected  x  Happiness[/C][/ROW]
[ROW][C] [/C][C]A[/C][C]B[/C][C]C[/C][C]D[/C][/ROW]
[C]A[/C][C]14.33[/C][C]20[/C][C]6.33[/C][C]13.33[/C][/ROW]
[C]B[/C][C]11.41[/C][C]15.93[/C][C]5.04[/C][C]10.62[/C][/ROW]
[C]C[/C][C]9.82[/C][C]13.7[/C][C]4.34[/C][C]9.14[/C][/ROW]
[C]D[/C][C]7.43[/C][C]10.37[/C][C]3.28[/C][C]6.91[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94831&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94831&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
Connected x Happiness
	A	B	C	D
A	14.33	20	6.33	13.33
B	11.41	15.93	5.04	10.62
C	9.82	13.7	4.34	9.14
D	7.43	10.37	3.28	6.91

Statistical Results
Pearson's Chi-squared test
Chi Square Statistic	12.47
Degrees of Freedom	9
P value	0.19

\begin{tabular}{lllllllll}
\hline
Statistical Results \tabularnewline
Pearson's Chi-squared test \tabularnewline
Chi Square Statistic & 12.47 \tabularnewline
Degrees of Freedom & 9 \tabularnewline
P value & 0.19 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94831&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]12.47[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]9[/C][/ROW]
[ROW][C]P value[/C][C]0.19[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94831&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94831&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	12.47
Degrees of Freedom	9
P value	0.19

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = 2 ; par3 = Pearson Chi-Squared ;

Parameters (R input):

par1 = 1 ; par2 = 2 ; 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