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Data X:
'7.5' 13 6 8 '6.5' 14 1 16 1 14 '5.5' 13 '8.5' 15 '6.5' 13 '4.5' 20 2 17 5 15 '0.5' 16 5 12 5 17 '2.5' 11 5 16 '5.5' 16 '3.5' 15 3 13 4 14 '0.5' 19 '6.5' 16 '4.5' 17 '7.5' 10 '5.5' 15 4 14 '7.5' 14 7 16 4 15 '5.5' 17 '2.5' 14 '5.5' 16 '3.5' 15 '2.5' 16 '4.5' 16 '4.5' 10 '4.5' 8 6 17 '2.5' 14 5 10 0 14 5 12 '6.5' 16 5 16 6 16 '4.5' 8 '5.5' 16 1 15 '7.5' 8 6 13 5 14 1 13 5 16 '6.5' 19 7 19 '4.5' 14 0 15 '8.5' 13 '3.5' 10 '7.5' 16 '3.5' 15 6 11 '1.5' 9 9 16 '3.5' 12 '3.5' 12 4 14 '6.5' 14 '7.5' 13 6 15 5 17 '5.5' 14 '3.5' 11 '7.5' 9 '6.5' 7 '6.5' 15 '6.5' 12 7 15 '3.5' 14 '1.5' 16 4 14 '7.5' 13 '4.5' 16 0 13 '3.5' 16 '5.5' 16 5 16 '4.5' 10 '2.5' 12 '7.5' 12 7 12 0 12 '4.5' 19 3 14 '1.5' 13 '3.5' 16 '2.5' 15 '5.5' 12 8 8 1 10 5 16 '4.5' 16 3 10 3 18 8 12 '2.5' 16 7 10 0 14 1 12 '3.5' 11 '5.5' 15 '5.5' 7 '0.5' 16 '7.5' 16 9 16 '9.5' 16 '8.5' 12 7 15 8 14 10 15 7 16 '8.5' 13 9 10 '9.5' 17 4 15 6 18 8 16 '5.5' 20 '9.5' 16 '7.5' 17 7 16 '7.5' 15 8 13 7 16 7 16 6 16 10 17 '2.5' 20 9 14 8 17 6 6 '8.5' 16 6 15 9 16 8 16 9 14 '5.5' 16 7 16 '5.5' 16 9 14 2 14 '8.5' 16 9 16 '8.5' 15 9 16 '7.5' 16 10 18 9 15 '7.5' 16 6 16 '10.5' 16 '8.5' 17 8 14 10 18 '10.5' 9 '6.5' 15 '9.5' 14 '8.5' 15 '7.5' 13 5 16 8 20 10 14 7 12 '7.5' 15 '7.5' 15 '9.5' 15 6 16 10 11 7 16 3 7 6 11 7 9 10 15 7 16 '3.5' 14 8 15 10 13 '5.5' 13 6 12 '6.5' 16 '6.5' 14 '8.5' 16 4 14 '9.5' 15 8 10 '8.5' 16 '5.5' 14 7 16 9 12 8 16 10 16 8 15 6 14 8 16 5 11 9 15 '4.5' 18 '8.5' 13 '9.5' 7 '8.5' 7 '7.5' 17 '7.5' 18 5 15 7 8 8 13 '5.5' 13 '8.5' 15 '9.5' 18 7 16 8 14 '8.5' 15 '3.5' 19 '6.5' 16 '6.5' 12 '10.5' 16 '8.5' 11 8 16 10 15 10 19 '9.5' 15 9 14 10 14 '7.5' 17 '4.5' 16 '4.5' 20 '0.5' 16 '6.5' 9 '4.5' 13 '5.5' 15 5 19 6 16 4 17 8 16 '10.5' 9 '6.5' 11 8 14 '8.5' 19 '5.5' 13 7 14 5 15 '3.5' 15 5 14 9 16 '8.5' 17 5 12 '9.5' 15 3 17 '1.5' 15 6 10 '0.5' 16 '6.5' 15 '7.5' 11 '4.5' 16 8 16 9 16 '7.5' 14 '8.5' 14 7 16 '9.5' 16 '6.5' 18 '9.5' 14 6 20 8 15 '9.5' 16 8 16 8 16 9 12 5 8
Names of X columns:
Ex 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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Big Analytics Cloud Computing Center
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