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R Software Module

rwasp_chi_squared_tests.wasp

Title produced by software

Chi-Squared and McNemar Tests

Date of computation

Mon, 15 Nov 2010 13:59:06 +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/t128982969496cmr2i8oio285h.htm/, Retrieved Sat, 27 Apr 2024 19:25:08 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=94835, Retrieved Sat, 27 Apr 2024 19:25:08 +0000

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No (this computation is public)

User-defined keywords

Estimated Impact

132

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] [dd4fe494cff2ee46c12b15bdc7b848ca]
F    D    [Chi-Squared and McNemar Tests] [] [2010-11-15 13:59:06] [6c31f786e793d35ef3a03978bc5de774] [Current]
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 08:46:34 [] [reply] 
Ook hier gebruiken we de Chi-Squared test met gesimuleerde p-value. En er is inderdaad een verband, maar positief of negatief? Het verband is negatief. Dit kan je afleiden uit de grafiek. Als je naar de 2 uitersten kijkt (A-A en D-D), dus naar de hoofddiagonaal, zie je dat de 2 balkjes onder de lijn liggen. Dus dat aantal studenten dat daar terechtkomen, komen minder voor dan verwacht. Maar als we dan de berekening opnieuw doen, maar dan voor 2 onderverdelingen, zien we dat de p-value 0,43 is. Dus dit zegt ons dat er geen verband is. Het is beter om hier van uit te gaan omdat het betrouwbaarder is om minder categorieën te hebben en een hogere cell-count.
2010-11-20 15:30:35 [48eb36e2c01435ad7e4ea7854a9d98fe] [reply] 
Zoals door de andere student reeds vermeld werd, dienen we hier (door de lage cell count) opnieuw te werken met 'Pearson's Chi-squared test with simulated p-value'. Een voorbeeld daarvan vindt men hier: http://www.freestatistics.org/blog/date/2010/Nov/16/t1289918499ipqwpijga0amdsq.htm/ 
 
Echter wanneer men in deze formule de gegevens ivm depression en connecter invuld, ziet men een zeer grote p waarde van 0,9. Dit betekent dat we de nulhypothese (er bestaat geen verband tussen beiden) aanvaarden. 
 
Ook wanneer we werken met de twee reeksen high en low (http://www.freestatistics.org/blog/date/2010/Nov/16/t1289921112lepehnnpifwxtov.htm/) komen we tot dezelfde conclusie.

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Dataseries X:

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Histogram

Boxplots

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

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	'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94835&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94835&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94835&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	'Gwilym Jenkins' @ 72.249.127.135

Tabulation of Results
Connected x Depression
	A	B	C	D
A	12	15	10	17
B	17	13	7	6
C	15	5	10	7
D	16	7	1	4

\begin{tabular}{lllllllll}
\hline
Tabulation of Results \tabularnewline
Connected  x  Depression \tabularnewline
  & A & B & C & D \tabularnewline
A & 12 & 15 & 10 & 17 \tabularnewline
B & 17 & 13 & 7 & 6 \tabularnewline
C & 15 & 5 & 10 & 7 \tabularnewline
D & 16 & 7 & 1 & 4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94835&T=1

[TABLE]
[ROW][C]Tabulation of Results[/C][/ROW]
[ROW][C]Connected  x  Depression[/C][/ROW]
[ROW][C] [/C][C]A[/C][C]B[/C][C]C[/C][C]D[/C][/ROW]
[C]A[/C][C]12[/C][C]15[/C][C]10[/C][C]17[/C][/ROW]
[C]B[/C][C]17[/C][C]13[/C][C]7[/C][C]6[/C][/ROW]
[C]C[/C][C]15[/C][C]5[/C][C]10[/C][C]7[/C][/ROW]
[C]D[/C][C]16[/C][C]7[/C][C]1[/C][C]4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94835&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94835&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 Depression
	A	B	C	D
A	12	15	10	17
B	17	13	7	6
C	15	5	10	7
D	16	7	1	4

Tabulation of Expected Results
Connected x Depression
	A	B	C	D
A	20	13.33	9.33	11.33
B	15.93	10.62	7.43	9.02
C	13.7	9.14	6.4	7.77
D	10.37	6.91	4.84	5.88

\begin{tabular}{lllllllll}
\hline
Tabulation of Expected Results \tabularnewline
Connected  x  Depression \tabularnewline
  & A & B & C & D \tabularnewline
A & 20 & 13.33 & 9.33 & 11.33 \tabularnewline
B & 15.93 & 10.62 & 7.43 & 9.02 \tabularnewline
C & 13.7 & 9.14 & 6.4 & 7.77 \tabularnewline
D & 10.37 & 6.91 & 4.84 & 5.88 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94835&T=2

[TABLE]
[ROW][C]Tabulation of Expected Results[/C][/ROW]
[ROW][C]Connected  x  Depression[/C][/ROW]
[ROW][C] [/C][C]A[/C][C]B[/C][C]C[/C][C]D[/C][/ROW]
[C]A[/C][C]20[/C][C]13.33[/C][C]9.33[/C][C]11.33[/C][/ROW]
[C]B[/C][C]15.93[/C][C]10.62[/C][C]7.43[/C][C]9.02[/C][/ROW]
[C]C[/C][C]13.7[/C][C]9.14[/C][C]6.4[/C][C]7.77[/C][/ROW]
[C]D[/C][C]10.37[/C][C]6.91[/C][C]4.84[/C][C]5.88[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94835&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94835&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 Depression
	A	B	C	D
A	20	13.33	9.33	11.33
B	15.93	10.62	7.43	9.02
C	13.7	9.14	6.4	7.77
D	10.37	6.91	4.84	5.88

Statistical Results
Pearson's Chi-squared test
Chi Square Statistic	18.74
Degrees of Freedom	9
P value	0.03

\begin{tabular}{lllllllll}
\hline
Statistical Results \tabularnewline
Pearson's Chi-squared test \tabularnewline
Chi Square Statistic & 18.74 \tabularnewline
Degrees of Freedom & 9 \tabularnewline
P value & 0.03 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94835&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]18.74[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]9[/C][/ROW]
[ROW][C]P value[/C][C]0.03[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94835&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94835&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	18.74
Degrees of Freedom	9
P value	0.03

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')

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Dataset

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Input Parameters & R Code