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 and McNemar Tests
Date of computationTue, 16 Nov 2010 10:52:42 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/16/t1289904776kx10wdhubj7zvob.htm/, Retrieved Sat, 04 May 2024 20:37:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=95369, Retrieved Sat, 04 May 2024 20:37:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi-Squared and McNemar Tests] [] [2010-11-14 13:57:53] [22937c5b58c14f6c22964f32d64ff823]
F   PD    [Chi-Squared and McNemar Tests] [workshop 6 Chi Sq...] [2010-11-16 10:52:42] [514029464b0621595fe21c9fa38c7009] [Current]
Feedback Forum
2010-11-20 18:18:13 [48eb36e2c01435ad7e4ea7854a9d98fe] [reply
De student heeft hier gebruik gemaakt van de correcte softwaremodule; de cell count is hier groter dan 5, dus mag men de bekomen resultaten interpreteren.

Maar de interpretatie van de student is niet correct. De nulhypothese waarop deze software gebaseerd is, is de volgende: er bestaat geen verband tussen beide reeksen. We zien hier een grote P waarde; namelijk 0,43. Een grote P waarde betekent dat we de de nulhypothese aanvaarden en dus stellen dat er geen verband is tussen Connected en Depression.

Echter wanneer we ons niet baseren op de 2 reeksen high en low, maar op de 4 reeksen A,B,C en D die ook opgenomen werden in het excel bestand, zien we andere resultaten. Aangezien de minimum cell count van 5 in dit geval niet steeds wordt bereikt, dienen we gebruik te maken van 'Pearson's Chi-squared test with simulated p-value'. Een voorbeeld is hier te vinden: http://www.freestatistics.org/blog/date/2010/Nov/16/t1289918417bny8q8pphln7ypv.htm/

In dit geval zien we een kleine P waarde, namelijk 0,02. Dit betekent dat we de nulhypothese verwerpen en dus aannemen dat er wel een verband bestaat tussen Connected en Depression. Daarom baseren we ons vervolgens op de 'associatie plot'. Deze grafische voorstelling leert ons dat er een negatief verband bestaat tussen beiden. Belangrijk is het dat we opmerken dat het bestaan van een verband niet betekent dat het gaat om een causaal verband.

Post a new message
Dataseries X:
'HI'	'HI'	'HI'	'HI'
'HI'	'LO'	'HI'	'LO'
'LO'	'HI'	'LO'	'HI'
'LO'	'LO'	'LO'	'HI'
'HI'	'HI'	'HI'	'HI'
'HI'	'LO'	'HI'	'HI'
'HI'	'LO'	'HI'	'HI'
'HI'	'HI'	'HI'	'LO'
'HI'	'HI'	'HI'	'LO'
'HI'	'HI'	'HI'	'HI'
'HI'	'LO'	'HI'	'LO'
'HI'	'HI'	'HI'	'LO'
'HI'	'HI'	'LO'	'HI'
'HI'	'HI'	'HI'	'HI'
'LO'	'HI'	'HI'	'LO'
'LO'	'LO'	'HI'	'HI'
'HI'	'LO'	'HI'	'HI'
'HI'	'HI'	'HI'	'LO'
'HI'	'HI'	'HI'	'LO'
'LO'	'LO'	'HI'	'HI'
'LO'	'LO'	'HI'	'LO'
'LO'	'LO'	'LO'	'HI'
'HI'	'HI'	'HI'	'HI'
'HI'	'HI'	'LO'	'HI'
'HI'	'LO'	'HI'	'LO'
'HI'	'LO'	'LO'	'LO'
'HI'	'HI'	'HI'	'LO'
'LO'	'HI'	'HI'	'HI'
'LO'	'LO'	'HI'	'HI'
'HI'	'LO'	'LO'	'HI'
'LO'	'LO'	'HI'	'LO'
'LO'	'LO'	'LO'	'HI'
'HI'	'LO'	'HI'	'LO'
'HI'	'HI'	'HI'	'LO'
'HI'	'LO'	'HI'	'HI'
'LO'	'LO'	'HI'	'LO'
'LO'	'LO'	'LO'	'HI'
'HI'	'LO'	'HI'	'HI'
'LO'	'LO'	'HI'	'LO'
'HI'	'LO'	'LO'	'LO'
'HI'	'LO'	'HI'	'LO'
'HI'	'LO'	'HI'	'HI'
'HI'	'LO'	'HI'	'LO'
'HI'	'LO'	'LO'	'HI'
'HI'	'LO'	'LO'	'LO'
'HI'	'HI'	'LO'	'HI'
'HI'	'HI'	'HI'	'LO'
'LO'	'HI'	'HI'	'LO'
'HI'	'HI'	'HI'	'HI'
'HI'	'LO'	'LO'	'LO'
'LO'	'HI'	'HI'	'LO'
'LO'	'LO'	'HI'	'HI'
'LO'	'LO'	'LO'	'HI'
'HI'	'HI'	'LO'	'HI'
'LO'	'LO'	'LO'	'LO'
'HI'	'LO'	'HI'	'HI'
'HI'	'HI'	'HI'	'HI'
'LO'	'HI'	'HI'	'LO'
'HI'	'HI'	'LO'	'LO'
'HI'	'HI'	'LO'	'HI'
'LO'	'LO'	'LO'	'HI'
'HI'	'HI'	'LO'	'HI'
'HI'	'HI'	'LO'	'HI'
'LO'	'HI'	'HI'	'HI'
'HI'	'LO'	'HI'	'HI'
'HI'	'HI'	'LO'	'LO'
'HI'	'HI'	'LO'	'HI'
'LO'	'LO'	'LO'	'HI'
'HI'	'HI'	'HI'	'HI'
'HI'	'HI'	'HI'	'HI'
'HI'	'HI'	'HI'	'HI'
'LO'	'HI'	'HI'	'HI'
'HI'	'HI'	'HI'	'HI'
'HI'	'HI'	'HI'	'LO'
'HI'	'LO'	'LO'	'LO'
'HI'	'LO'	'LO'	'HI'
'HI'	'HI'	'HI'	'HI'
'HI'	'LO'	'LO'	'HI'
'LO'	'LO'	'HI'	'HI'
'HI'	'LO'	'LO'	'LO'
'LO'	'HI'	'HI'	'LO'
'HI'	'HI'	'HI'	'LO'
'HI'	'HI'	'HI'	'LO'
'HI'	'LO'	'HI'	'HI'
'LO'	'HI'	'HI'	'HI'
'LO'	'LO'	'HI'	'HI'
'HI'	'HI'	'HI'	'HI'
'LO'	'HI'	'HI'	'HI'
'LO'	'LO'	'LO'	'HI'
'LO'	'LO'	'LO'	'HI'
'LO'	'HI'	'HI'	'HI'
'HI'	'LO'	'LO'	'HI'
'HI'	'HI'	'HI'	'HI'
'LO'	'LO'	'HI'	'HI'
'LO'	'LO'	'LO'	'LO'
'HI'	'HI'	'HI'	'LO'
'HI'	'HI'	'LO'	'HI'
'HI'	'LO'	'HI'	'LO'
'HI'	'HI'	'HI'	'LO'
'LO'	'HI'	'HI'	'LO'
'HI'	'HI'	'HI'	'LO'
'HI'	'HI'	'LO'	'HI'
'HI'	'HI'	'HI'	'HI'
'LO'	'LO'	'LO'	'LO'
'LO'	'HI'	'HI'	'HI'
'HI'	'LO'	'LO'	'HI'
'HI'	'HI'	'HI'	'LO'
'HI'	'HI'	'HI'	'HI'
'HI'	'HI'	'LO'	'HI'
'HI'	'HI'	'LO'	'HI'
'LO'	'HI'	'HI'	'HI'
'LO'	'LO'	'LO'	'HI'
'LO'	'HI'	'LO'	'LO'
'LO'	'LO'	'HI'	'HI'
'HI'	'HI'	'HI'	'HI'
'HI'	'LO'	'HI'	'LO'
'LO'	'HI'	'HI'	'HI'
'HI'	'HI'	'HI'	'HI'
'LO'	'HI'	'HI'	'LO'
'HI'	'HI'	'HI'	'HI'
'LO'	'HI'	'LO'	'HI'
'LO'	'LO'	'HI'	'HI'
'HI'	'HI'	'HI'	'LO'
'HI'	'HI'	'HI'	'LO'
'LO'	'LO'	'HI'	'LO'
'LO'	'LO'	'LO'	'LO'
'HI'	'LO'	'HI'	'LO'
'HI'	'HI'	'HI'	'LO'
'LO'	'HI'	'HI'	'LO'
'HI'	'LO'	'HI'	'HI'
'LO'	'LO'	'LO'	'LO'
'LO'	'LO'	'LO'	'HI'
'HI'	'HI'	'HI'	'LO'
'LO'	'LO'	'HI'	'HI'
'HI'	'HI'	'HI'	'HI'
'LO'	'LO'	'HI'	'HI'
'LO'	'LO'	'LO'	'HI'
'HI'	'HI'	'HI'	'HI'
'LO'	'HI'	'LO'	'HI'
'HI'	'HI'	'HI'	'LO'
'LO'	'HI'	'LO'	'HI'
'LO'	'HI'	'HI'	'LO'
'LO'	'HI'	'HI'	'HI'
'LO'	'HI'	'HI'	'HI'
'LO'	'LO'	'HI'	'HI'
'HI'	'LO'	'HI'	'LO'
'LO'	'LO'	'HI'	'HI'
'HI'	'HI'	'LO'	'HI'
'LO'	'LO'	'LO'	'LO'
'HI'	'LO'	'LO'	'HI'
'HI'	'HI'	'HI'	'HI'
'HI'	'HI'	'LO'	'HI'
'HI'	'HI'	'HI'	'LO'
'HI'	'HI'	'LO'	'HI'
'HI'	'HI'	'LO'	'HI'
'LO'	'LO'	'LO'	'HI'
'HI'	'LO'	'LO'	'HI'
'LO'	'HI'	'HI'	'HI'
'LO'	'HI'	'HI'	'LO'
'HI'	'LO'	'LO'	'LO'
'LO'	'HI'	'LO'	'HI'
'HI'	'HI'	'LO'	'HI'




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 3 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95369&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95369&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95369&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Tabulation of Results
Connected x Depression
HILO
HI5740
LO4322

\begin{tabular}{lllllllll}
\hline
Tabulation of Results \tabularnewline
Connected  x  Depression \tabularnewline
  & HI & LO \tabularnewline
HI & 57 & 40 \tabularnewline
LO & 43 & 22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95369&T=1

[TABLE]
[ROW][C]Tabulation of Results[/C][/ROW]
[ROW][C]Connected  x  Depression[/C][/ROW]
[ROW][C] [/C][C]HI[/C][C]LO[/C][/ROW]
[C]HI[/C][C]57[/C][C]40[/C][/ROW]
[C]LO[/C][C]43[/C][C]22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95369&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95369&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
HILO
HI5740
LO4322







Tabulation of Expected Results
Connected x Depression
HILO
HI59.8837.12
LO40.1224.88

\begin{tabular}{lllllllll}
\hline
Tabulation of Expected Results \tabularnewline
Connected  x  Depression \tabularnewline
  & HI & LO \tabularnewline
HI & 59.88 & 37.12 \tabularnewline
LO & 40.12 & 24.88 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95369&T=2

[TABLE]
[ROW][C]Tabulation of Expected Results[/C][/ROW]
[ROW][C]Connected  x  Depression[/C][/ROW]
[ROW][C] [/C][C]HI[/C][C]LO[/C][/ROW]
[C]HI[/C][C]59.88[/C][C]37.12[/C][/ROW]
[C]LO[/C][C]40.12[/C][C]24.88[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95369&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95369&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
HILO
HI59.8837.12
LO40.1224.88







Statistical Results
Pearson's Chi-squared test with Yates' continuity correction
Chi Square Statistic0.61
Degrees of Freedom1
P value0.43

\begin{tabular}{lllllllll}
\hline
Statistical Results \tabularnewline
Pearson's Chi-squared test with Yates' continuity correction \tabularnewline
Chi Square Statistic & 0.61 \tabularnewline
Degrees of Freedom & 1 \tabularnewline
P value & 0.43 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=95369&T=3

[TABLE]
[ROW][C]Statistical Results[/C][/ROW]
[ROW][C]Pearson's Chi-squared test with Yates' continuity correction[/C][/ROW]
[ROW][C]Chi Square Statistic[/C][C]0.61[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]1[/C][/ROW]
[ROW][C]P value[/C][C]0.43[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=95369&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=95369&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 with Yates' continuity correction
Chi Square Statistic0.61
Degrees of Freedom1
P value0.43



Parameters (Session):
par1 = 1 ; par2 = 4 ; par3 = Pearson Chi-Squared ;
Parameters (R input):
par1 = 1 ; par2 = 4 ; 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')