Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
1 50 1 68 1 62 1 54 1 71 1 54 1 65 1 73 1 52 1 84 1 42 1 66 1 65 1 73 1 75 0 72 1 66 1 70 1 81 1 69 1 71 1 68 1 70 0 68 1 67 1 76 1 70 1 60 1 72 1 71 1 70 0 64 1 76 1 68 1 76 0 65 1 67 0 75 1 60 0 73 1 63 1 70 1 66 1 64 1 70 1 75 1 60 1 66 1 59 1 78 1 67 0 59 1 66 1 71 0 66 0 72 0 71 0 59 0 78 0 65 0 65 0 71 0 72 0 66 0 69 1 51 1 56 1 67 1 69 0 57 0 56 1 55 1 63 1 67 1 65 1 47 1 76 1 64 1 68 1 64 1 65 0 71 1 63 1 60 1 68 1 72 1 70 1 61 1 61 1 62 1 71 1 71 1 51 0 56 1 70 1 73 1 76 1 59 1 68 1 48 1 52 1 59 1 60 1 59 1 57 1 79 1 60 1 60 1 59 0 62 0 59 1 61 1 71 0 57 0 66 0 63 0 69 1 58 1 59 0 48 0 66 0 73 0 67 0 61 0 68 0 75 0 62 0 69 1 58 1 60 0 74 1 55 1 62 0 63 1 69 0 58 0 58 1 68 0 72 0 62 0 62 0 65 0 69 0 66 0 72 0 62 0 75 0 58 0 66 0 55 0 47 1 72 0 62 0 64 0 64 1 19 0 50 1 68 0 70 1 79 0 69 1 71 0 48 0 66 0 73 0 74 0 66 1 71 1 74 0 78 1 75 1 53 0 60 1 50 1 70 0 69 0 65 1 78 0 78 1 59 1 72 1 70 0 63 1 63 0 71 1 74 1 67 1 66 1 62 0 80 1 73 1 67 1 61 0 73 1 74 1 32 0 69 1 69 0 84 0 64 0 58 1 60 0 59 0 78 1 57 1 60 1 68 1 68 1 73 1 69 0 67 0 60 1 65 0 66 0 74 1 81 0 72 0 55 0 49 0 74 0 53 0 64 0 65 0 57 0 51 0 80 0 67 0 70 0 74 0 75 0 70 0 69 0 65 1 55 0 71 0 65
Names of X columns:
s/b_(s_=_1) AMS.E
Factor 1
Factor 2
Type of test to use
(?)
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')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation