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Data X:
12 13 8 8 11 14 13 16 11 14 10 13 7 15 10 13 15 20 12 17 12 15 10 16 10 12 14 17 6 11 12 16 14 16 11 15 8 13 12 14 15 19 13 16 11 17 12 10 7 15 11 14 7 14 12 16 12 15 13 17 9 14 11 16 12 15 15 16 12 16 6 10 5 8 13 17 11 14 6 10 12 14 10 12 6 16 12 16 11 16 6 8 12 16 12 15 8 8 10 13 11 14 7 13 12 16 13 19 14 19 12 14 6 15 14 13 10 10 12 16 11 15 10 11 7 9 12 16 7 12 12 12 12 14 10 14 10 13 12 15 12 17 12 14 8 11 10 9 5 7 10 15 12 12 11 15 9 14 12 16 11 14 10 13 12 16 10 13 9 16 11 16 12 16 7 10 11 12 12 12 6 12 9 12 15 19 10 14 11 13 12 16 12 15 12 12 11 8 9 10 11 16 12 16 12 10 14 18 8 12 10 16 9 10 10 14 9 12 10 11 12 15 11 7 9 16 11 16 12 16 12 16 7 12 12 15 12 14 12 15 10 16 15 13 10 10 15 17 10 15 15 18 9 16 15 20 12 16 13 17 12 16 12 15 8 13 9 16 15 16 12 16 12 17 15 20 11 14 12 17 6 6 14 16 12 15 12 16 12 16 11 14 12 16 12 16 12 16 12 14 8 14 8 16 12 16 12 15 11 16 10 16 11 18 12 15 13 16 12 16 12 16 10 17 10 14 11 18 8 9 12 15 9 14 12 15 9 13 11 16 15 20 8 14 8 12 11 15 11 15 11 15 13 16 7 11 12 16 8 7 8 11 4 9 11 15 10 16 7 14 12 15 11 13 9 13 10 12 8 16 8 14 11 16 12 14 10 15 10 10 12 16 8 14 11 16 8 12 10 16 14 16 9 15 9 14 10 16 13 11 12 15 13 18 8 13 3 7 8 7 12 17 11 18 9 15 12 8 12 13 12 13 10 15 13 18 9 16 12 14 11 15 14 19 11 16 9 12 12 16 8 11 15 16 12 15 14 19 12 15 9 14 9 14 13 17 13 16 15 20 11 16 7 9 10 13 11 15 14 19 14 16 13 17 12 16 8 9 13 11 9 14 12 19 13 13 11 14 11 15 13 15 12 14 12 16 10 17 9 12 10 15 13 17 13 15 9 10 11 16 12 15 8 11 12 16 12 16 12 16 9 14 12 14 12 16 11 16 12 18 6 14 7 20 10 15 12 16 10 16 12 16 9 12
Names of X columns:
CONFSOFTTOT CONFSTATTOT
Factor 1
Factor 2
Type of test to use
(?)
Pearson Chi-Squared
Pearson Chi-Squared
Exact Pearson Chi-Squared by Simulation
McNemar Chi-Squared
Fisher Exact Test
Chart options
Title:
R Code
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')
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Summary of computational transaction
Raw Input
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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