Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_chi_squared_tests.wasp
Title produced by softwareChi-Squared Test, McNemar Test, and Fisher Exact Test
Date of computationTue, 15 Dec 2020 16:17:23 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2020/Dec/15/t160804558699o1iw63afw5bq4.htm/, Retrieved Sun, 13 Jun 2021 02:40:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319322, Retrieved Sun, 13 Jun 2021 02:40:43 +0000
QR Codes:

Original text written by user:Chi² lukt niet met deze gegevens. Ook sexLabel - chestpainLabel
IsPrivate?No (this computation is public)
User-defined keywordsError
Estimated Impact23
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] [sexLabel - fastin...] [2020-12-15 15:17:23] [6bc9d4468c877d2b2e49ed1288c7c75d] [Current]
Feedback Forum

Post a new message
Dataseries X:
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'greater than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'greater than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'greater than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'greater than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Female' "'greater than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Female' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Female' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Female' "'lower than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Male' "'greater than 120mg/ml'"
'Male' "'lower than 120mg/ml'"
'Female' "'lower than 120mg/ml'"




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center
R Engine error message
Error in array(list("Male", "'greater,than,120mg/ml'", "Male", "'lower,than,120mg/ml'",  : 
  length of 'dimnames' [1] not equal to array extent
Execution halted

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
R Engine error message & 
Error in array(list("Male", "'greater,than,120mg/ml'", "Male", "'lower,than,120mg/ml'",  : 
  length of 'dimnames' [1] not equal to array extent
Execution halted
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=319322&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [ROW]R Engine error message[/C][C]
Error in array(list("Male", "'greater,than,120mg/ml'", "Male", "'lower,than,120mg/ml'",  : 
  length of 'dimnames' [1] not equal to array extent
Execution halted
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319322&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319322&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 Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center
R Engine error message
Error in array(list("Male", "'greater,than,120mg/ml'", "Male", "'lower,than,120mg/ml'",  : 
  length of 'dimnames' [1] not equal to array extent
Execution halted



Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = Exact Pearson Chi-Squared by Simulation ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = Exact Pearson Chi-Squared by Simulation ;
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')