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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 Test, McNemar Test, and Fisher Exact Test

Date of computation

Mon, 08 Dec 2014 16:49:30 +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/2014/Dec/08/t1418057393vdjecitdn0fyyvg.htm/, Retrieved Tue, 10 Feb 2026 19:26:40 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264086, Retrieved Tue, 10 Feb 2026 19:26:40 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

271

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

-       [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [Chi-SQ calculatio...] [2014-12-08 16:49:30] [e719845b3f21bd57beb5defeff8ed9b5] [Current]

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Dataseries X:

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Histogram

Boxplots

'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Average'	'Strong'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Strong'
'Weak'	'Weak'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Weak'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Weak'	'Weak'
'Strong'	'Strong'
'Strong'	'Strong'
'Strong'	'Strong'
'Average'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Weak'
'Strong'	'Weak'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Strong'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Weak'	'Weak'
'Strong'	'Strong'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Weak'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Weak'	'Average'
'Average'	'Average'
'Strong'	'Weak'
'Average'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Strong'
'Average'	'Average'
'Strong'	'Strong'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Average'	'Weak'
'Average'	'Weak'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Average'	'Weak'
'Strong'	'Weak'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Average'	'Average'
'Strong'	'Weak'
'Weak'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Weak'
'Average'	'Average'
'Weak'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Average'	'Average'
'Strong'	'Strong'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Weak'
'Average'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Strong'
'Strong'	'Strong'
'Strong'	'Strong'
'Strong'	'Strong'
'Strong'	'Strong'
'Weak'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Average'
'Strong'	'Strong'
'Strong'	'Strong'
'Weak'	'Weak'
'Average'	'Weak'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Average'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Weak'	'Weak'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Weak'
'Strong'	'Strong'
'Average'	'Weak'
'Average'	'Average'
'Average'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Strong'
'Average'	'Average'
'Average'	'Weak'
'Strong'	'Strong'
'Average'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Weak'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Strong'
'Strong'	'Strong'
'Average'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Average'	'Weak'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Weak'	'Weak'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Strong'
'Strong'	'Weak'
'Strong'	'Average'
'Weak'	'Average'
'Average'	'Weak'
'Average'	'Average'
'Strong'	'Strong'
'Average'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Average'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Average'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Weak'	'Average'
'Average'	'Weak'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Average'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Strong'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Average'
'Average'	'Strong'
'Average'	'Average'
'Average'	'Average'
'Average'	'Average'
'Average'	'Weak'
'Average'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Strong'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Average'	'Strong'
'Average'	'Weak'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Average'	'Weak'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Strong'
'Strong'	'Strong'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Average'	'Average'
'Average'	'Weak'
'Strong'	'Strong'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Strong'
'Strong'	'Weak'
'Average'	'Weak'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Average'	'Strong'
'Strong'	'Average'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Average'	'Average'
'Average'	'Strong'
'Strong'	'Strong'
'Strong'	'Strong'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Weak'	'Weak'
'Average'	'Weak'
'Strong'	'Weak'
'Average'	'Average'
'Average'	'Weak'
'Average'	'Average'
'Strong'	'Weak'
'Weak'	'Average'
'Average'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Weak'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Strong'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Weak'
'Average'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Strong'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Average'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Average'
'Strong'	'Strong'
'Average'	'Average'
'Average'	'Weak'
'Weak'	'Weak'
'Strong'	'Average'
'Weak'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Weak'
'Strong'	'Weak'
'Average'	'Average'
'Strong'	'Weak'
'Strong'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Average'
'Average'	'Average'
'Weak'	'Average'
'Strong'	'Weak'
'Strong'	'Weak'
'Average'	'Average'
'Average'	'Average'
'Average'	'Weak'
'Strong'	'Weak'
'Average'	'Weak'
'Strong'	'Weak'
'Average'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Average'	'Strong'
'Strong'	'Average'
'Weak'	'Weak'
'Average'	'Average'
'Average'	'Average'
'Average'	'Weak'
'Average'	'Weak'
'Weak'	'Weak'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Average'	'Weak'
'Strong'	'Average'
'Average'	'Weak'
'Weak'	'Weak'
'Strong'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Average'	'Average'
'Strong'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Average'
'Weak'	'Weak'
'Weak'	'Average'
'Strong'	'Weak'
'Average'	'Weak'
'Strong'	'Weak'
'Strong'	'Weak'
'Strong'	'Weak'
'Strong'	'Strong'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Weak'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Strong'	'Weak'
'Average'	'Weak'
'Strong'	'Weak'
'Average'	'Average'
'Average'	'Average'
'Average'	'Weak'
'Average'	'Average'
'Strong'	'Strong'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Weak'
'Average'	'Average'
'Strong'	'Weak'
'Average'	'Weak'
'Strong'	'Average'
'Weak'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Strong'
'Average'	'Average'
'Strong'	'Average'
'Weak'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Weak'	'Average'
'Strong'	'Weak'
'Strong'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Strong'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Average'	'Average'
'Strong'	'Weak'
'Average'	'Weak'
'Average'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Strong'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Average'	'Weak'
'Strong'	'Strong'
'Strong'	'Weak'
'Strong'	'Weak'
'Average'	'Average'
'Weak'	'Weak'
'Strong'	'Average'
'Strong'	'Strong'
'Average'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Average'	'Weak'
'Weak'	'Weak'
'Average'	'Weak'
'Strong'	'Weak'
'Average'	'Strong'
'Average'	'Weak'
'Strong'	'Average'
'Strong'	'Weak'
'Average'	'Weak'
'Strong'	'Weak'
'Strong'	'Strong'
'Average'	'Weak'
'Average'	'Weak'
'Strong'	'Strong'
'Average'	'Average'
'Strong'	'Weak'
'Strong'	'Weak'
'Strong'	'Weak'
'Average'	'Weak'
'Weak'	'Weak'
'Strong'	'Weak'
'Strong'	'Average'
'Strong'	'Average'
'Strong'	'Average'
'Average'	'Weak'
'Average'	'Weak'

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	'Herman Ole Andreas Wold' @ wold.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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264086&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264086&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264086&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	'Herman Ole Andreas Wold' @ wold.wessa.net

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=='Fisher Exact Test') {
(cst <- fisher.test(table1))
}
if ((par3 != 'McNemar Chi-Squared') & (par3 != 'Fisher Exact Test')) {
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)
if (par3=='Pearson Chi-Squared') a<-table.element(a, 'Pearson Chi Square Statistic', 1, TRUE)
if (par3=='Exact Pearson Chi-Squared by Simulation') a<-table.element(a, 'Exact Pearson Chi Square Statistic', 1, TRUE)
if (par3=='McNemar Chi-Squared') a<-table.element(a, 'McNemar Chi Square Statistic', 1, TRUE)
if (par3=='Fisher Exact Test') a<-table.element(a, 'Odds Ratio', 1, TRUE)
if (par3=='Fisher Exact Test') {
if ((ncol(table1) == 2) & (nrow(table1) == 2)) {
a<-table.element(a, round(cst$estimate, digits=2), 1,FALSE)
} else {
a<-table.element(a, '--', 1,FALSE)
}
} else {
a<-table.element(a, round(cst$statistic, digits=2), 1,FALSE)
}
a<-table.row.end(a)
if(!simulate.p.value){
if(par3!='Fisher Exact Test') {
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