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Data X:
19 18 20 24 24 19 15 16 12 17 19 16 19 15 9 28 28 28 26 21 20 15 18 16 26 22 22 16 19 17 15 16 12 22 18 16 26 24 15 26 20 17 21 19 17 22 23 18 20 18 15 21 16 20 22 21 21 18 27 6 20 19 19 24 7 12 17 20 14 20 20 13 20 19 17 22 20 19 15 14 10 20 17 11 22 17 11 17 8 10 14 9 7 17 20 12 23 20 18 16 22 9 18 22 16 20 16 14 18 14 11 23 24 20 24 21 17 23 20 14 20 18 16 19 19 10 22 24 15 17 16 10 20 14 10 21 21 16 21 15 10 23 21 22 15 17 13 22 19 18 17 13 8 19 18 16 21 17 21 21 20 17 24 18 18 19 18 15 14 12 8 25 22 22 17 18 13 20 20 18 22 20 15 15 16 11 23 22 19 20 19 19 16 6 4 25 19 17 18 24 10 23 18 20 20 17 15 6 6 4 15 22 9 18 20 18 22 16 17 21 17 12 20 23 17 25 22 20 16 20 16 20 20 15 14 13 10 22 16 16 26 25 21 20 16 15 17 15 16 22 19 9 20 24 19 17 9 7 22 22 23 17 15 14 22 22 10 25 24 12 11 12 10 19 21 7 24 25 20 17 26 9 26 28 19 21 16 14 21 21 14 19 22 15 24 20 22 28 19 19 27 24 22 23 18 17 22 22 17 15 18 17 20 23 11 28 28 24 19 21 16 22 21 13 21 20 15 20 18 15 19 17 11 17 17 13 21 23 7 12 14 9 20 21 12 18 14 14 21 24 22 24 16 19 17 17 16 8 17 22 22 21 20 17 19 15 25 19 11 18 11 9 23 15 18 21 18 11 21 19 14 24 23 10 17 16 16 15 11 11 22 21 16 19 14 13 19 20 14 19 19 10 22 21 19 23 22 17 25 23 19 20 18 12 23 23 8 21 20 17 23 23 17 11 13 7 21 21 23 21 19 17 22 19 13 21 18 8 22 19 16 18 10 13 24 24 15 20 21 15 18 18 14 14 16 11 17 20 19 18 12 12 19 15 18 15 14 15 24 18 20 19 19 12 23 24 19 23 21 18 17 22 8 22 20 18 16 16 13 21 19 18 19 19 13 13 7 10 17 17 12 18 23 10 20 23 13 18 18 8 15 18 9 17 15 12 21 14 11 23 17 10 18 20 16 20 21 14 22 18 19 20 18 16 24 21 21 23 16 16 22 17 12 21 12 9 23 25 15 20 12 11 23 22 20 24 24 19 17 18 17 19 15 18 25 25 19 18 17 11 15 17 8 27 24 19 26 27 24 14 19 8 19 22 10 25 24 20 20 23 17 17 16 12 13 16 10 20 16 15 20 15 16 18 17 16 22 25 18 21 14 16 18 20 20 19 19 16 23 18 11 26 22 24 19 18 13 26 22 17 23 18 9 23 19 10 23 21 15 20 20 12 16 17 12 26 22 22 24 24 23 20 19 19 12 20 7 21 16 9 26 22 19 17 19 8 18 13 10 28 22 18 24 20 19 24 21 12 12 15 12 13 15 10 16 23 12 23 21 15 18 16 13 18 18 14 21 18 18 7 10 4 21 20 10 17 13 7 22 25 20 15 18 10 10 19 11 25 17 16 23 22 19 23 19 16 23 21 15 23 21 14 15 15 11 23 22 11 23 21 19 23 20 15 17 18 12 19 19 24 23 21 16 22 19 9 14 16 16 19 17 8 21 26 11 23 20 13 16 13 14 19 21 14 26 23 17 22 20 20 24 23 11 24 24 19 11 8 6 21 19 16 21 18 14 22 21 16 19 16 11 18 17 14 27 27 22 14 12 7 15 17 17 20 17 16 26 24 22 20 18 13 19 18 14 20 19 15 18 19 15 20 24 15 26 22 19 20 20 18 21 22 10
Names of X columns:
AMS.I1 AMS.I2 AMS.I3
Scale (list separated by spaces)
R Code
docor <- function(x,y,method) { r <- cor.test(x,y,method=method) paste(round(r$estimate,3),' (',round(r$p.value,3),')',sep='') } x <- t(x) nx <- length(x[,1]) cx <- length(x[1,]) mymedian <- median(as.numeric(strsplit(par1,' ')[[1]])) myresult <- array(NA, dim = c(cx,7)) rownames(myresult) <- paste('Q',1:cx,sep='') colnames(myresult) <- c('mean','Sum of<br />positives (Ps)','Sum of<br />negatives (Ns)', '(Ps-Ns)/(Ps+Ns)', 'Count of<br />positives (Pc)', 'Count of<br />negatives (Nc)', '(Pc-Nc)/(Pc+Nc)') for (i in 1:cx) { spos <- 0 sneg <- 0 cpos <- 0 cneg <- 0 for (j in 1:nx) { if (!is.na(x[j,i])) { myx <- as.numeric(x[j,i]) - mymedian if (myx > 0) { spos = spos + myx cpos = cpos + 1 } if (myx < 0) { sneg = sneg + abs(myx) cneg = cneg + 1 } } } myresult[i,1] <- round(mean(as.numeric(x[,i]),na.rm=T)-mymedian,2) myresult[i,2] <- spos myresult[i,3] <- sneg myresult[i,4] <- round((spos - sneg) / (spos + sneg),2) myresult[i,5] <- cpos myresult[i,6] <- cneg myresult[i,7] <- round((cpos - cneg) / (cpos + cneg),2) } myresult load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Summary of survey scores (median of Likert score was subtracted)',8,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Question',header=TRUE) for (i in 1:7) { a<-table.element(a,colnames(myresult)[i],header=TRUE) } a<-table.row.end(a) for (i in 1:cx) { a<-table.row.start(a) a<-table.element(a,i,header=TRUE) for (j in 1:7) { a<-table.element(a,myresult[i,j],align='right') } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Pearson correlations of survey scores (and p-values)',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'',header=TRUE) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE) a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,docor(myresult[,1],myresult[,1],method='pearson'),align='right') a<-table.element(a,docor(myresult[,1],myresult[,4],method='pearson'),align='right') a<-table.element(a,docor(myresult[,1],myresult[,7],method='pearson'),align='right') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE) a<-table.element(a,docor(myresult[,4],myresult[,1],method='pearson'),align='right') a<-table.element(a,docor(myresult[,4],myresult[,4],method='pearson'),align='right') a<-table.element(a,docor(myresult[,4],myresult[,7],method='pearson'),align='right') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE) a<-table.element(a,docor(myresult[,7],myresult[,1],method='pearson'),align='right') a<-table.element(a,docor(myresult[,7],myresult[,4],method='pearson'),align='right') a<-table.element(a,docor(myresult[,7],myresult[,7],method='pearson'),align='right') 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,'Kendall tau rank correlations of survey scores (and p-values)',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'',header=TRUE) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE) a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,docor(myresult[,1],myresult[,1],method='kendall'),align='right') a<-table.element(a,docor(myresult[,1],myresult[,4],method='kendall'),align='right') a<-table.element(a,docor(myresult[,1],myresult[,7],method='kendall'),align='right') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE) a<-table.element(a,docor(myresult[,4],myresult[,1],method='kendall'),align='right') a<-table.element(a,docor(myresult[,4],myresult[,4],method='kendall'),align='right') a<-table.element(a,docor(myresult[,4],myresult[,7],method='kendall'),align='right') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE) a<-table.element(a,docor(myresult[,7],myresult[,1],method='kendall'),align='right') a<-table.element(a,docor(myresult[,7],myresult[,4],method='kendall'),align='right') a<-table.element(a,docor(myresult[,7],myresult[,7],method='kendall'),align='right') 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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