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Data X:
2 41 38 14 12 2 39 32 18 11 2 30 35 11 14 1 31 33 12 12 2 34 37 16 21 2 35 29 18 12 2 39 31 14 22 2 34 36 14 11 2 36 35 15 10 2 37 38 15 13 1 38 31 17 10 2 36 34 19 8 1 38 35 10 15 2 39 38 16 14 2 33 37 18 10 1 32 33 14 14 1 36 32 14 14 2 38 38 17 11 1 39 38 14 10 2 32 32 16 13 1 32 33 18 7 2 31 31 11 14 2 39 38 14 12 2 37 39 12 14 1 39 32 17 11 2 41 32 9 9 1 36 35 16 11 2 33 37 14 15 2 33 33 15 14 1 34 33 11 13 2 31 28 16 9 1 27 32 13 15 2 37 31 17 10 2 34 37 15 11 1 34 30 14 13 1 32 33 16 8 1 29 31 9 20 1 36 33 15 12 2 29 31 17 10 1 35 33 13 10 1 37 32 15 9 2 34 33 16 14 1 38 32 16 8 1 35 33 12 14 2 38 28 12 11 2 37 35 11 13 2 38 39 15 9 2 33 34 15 11 2 36 38 17 15 1 38 32 13 11 2 32 38 16 10 1 32 30 14 14 1 32 33 11 18 2 34 38 12 14 1 32 32 12 11 2 37 32 15 12 2 39 34 16 13 2 29 34 15 9 1 37 36 12 10 2 35 34 12 15 1 30 28 8 20 1 38 34 13 12 2 34 35 11 12 2 31 35 14 14 2 34 31 15 13 1 35 37 10 11 2 36 35 11 17 1 30 27 12 12 2 39 40 15 13 1 35 37 15 14 1 38 36 14 13 2 31 38 16 15 2 34 39 15 13 1 38 41 15 10 1 34 27 13 11 2 39 30 12 19 2 37 37 17 13 2 34 31 13 17 1 28 31 15 13 1 37 27 13 9 1 33 36 15 11 1 37 38 16 10 2 35 37 15 9 1 37 33 16 12 2 32 34 15 12 2 33 31 14 13 1 38 39 15 13 2 33 34 14 12 2 29 32 13 15 2 33 33 7 22 2 31 36 17 13 2 36 32 13 15 2 35 41 15 13 2 32 28 14 15 2 29 30 13 10 2 39 36 16 11 2 37 35 12 16 2 35 31 14 11 1 37 34 17 11 1 32 36 15 10 2 38 36 17 10 1 37 35 12 16 2 36 37 16 12 1 32 28 11 11 2 33 39 15 16 1 40 32 9 19 2 38 35 16 11 1 41 39 15 16 1 36 35 10 15 2 43 42 10 24 2 30 34 15 14 2 31 33 11 15 2 32 41 13 11 1 32 33 14 15 2 37 34 18 12 1 37 32 16 10 2 33 40 14 14 2 34 40 14 13 2 33 35 14 9 2 38 36 14 15 2 33 37 12 15 2 31 27 14 14 2 38 39 15 11 2 37 38 15 8 2 33 31 15 11 2 31 33 13 11 1 39 32 17 8 2 44 39 17 10 2 33 36 19 11 2 35 33 15 13 1 32 33 13 11 1 28 32 9 20 2 40 37 15 10 1 27 30 15 15 1 37 38 15 12 2 32 29 16 14 1 28 22 11 23 1 34 35 14 14 2 30 35 11 16 2 35 34 15 11 1 31 35 13 12 2 32 34 15 10 1 30 34 16 14 2 30 35 14 12 1 31 23 15 12 2 40 31 16 11 2 32 27 16 12 1 36 36 11 13 1 32 31 12 11 1 35 32 9 19 2 38 39 16 12 2 42 37 13 17 1 34 38 16 9 2 35 39 12 12 2 35 34 9 19 2 33 31 13 18 2 36 32 13 15 2 32 37 14 14 2 33 36 19 11 2 34 32 13 9 2 32 35 12 18 2 34 36 13 16
Names of X columns:
Gender Connected Separate Happiness Depression
Type of Correlation
kendall
pearson
spearman
kendall
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R Code
panel.tau <- function(x, y, digits=2, prefix='', cex.cor) { usr <- par('usr'); on.exit(par(usr)) par(usr = c(0, 1, 0, 1)) rr <- cor.test(x, y, method=par1) r <- round(rr$p.value,2) txt <- format(c(r, 0.123456789), digits=digits)[1] txt <- paste(prefix, txt, sep='') if(missing(cex.cor)) cex <- 0.5/strwidth(txt) text(0.5, 0.5, txt, cex = cex) } panel.hist <- function(x, ...) { usr <- par('usr'); on.exit(par(usr)) par(usr = c(usr[1:2], 0, 1.5) ) h <- hist(x, plot = FALSE) breaks <- h$breaks; nB <- length(breaks) y <- h$counts; y <- y/max(y) rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...) } bitmap(file='test1.png') pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main) dev.off() load(file='createtable') n <- length(y[,1]) n a<-table.start() a<-table.row.start(a) a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,' ',header=TRUE) for (i in 1:n) { a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE) } a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE) for (j in 1:n) { r <- cor.test(y[i,],y[j,],method=par1) a<-table.element(a,round(r$estimate,3)) } 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,'Correlations for all pairs of data series with p-values',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'pair',1,TRUE) a<-table.element(a,'Pearson r',1,TRUE) a<-table.element(a,'Spearman rho',1,TRUE) a<-table.element(a,'Kendall tau',1,TRUE) a<-table.row.end(a) cor.test(y[1,],y[2,],method=par1) for (i in 1:(n-1)) { for (j in (i+1):n) { a<-table.row.start(a) dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='') a<-table.element(a,dum,header=TRUE) rp <- cor.test(y[i,],y[j,],method='pearson') a<-table.element(a,round(rp$estimate,4)) rs <- cor.test(y[i,],y[j,],method='spearman') a<-table.element(a,round(rs$estimate,4)) rk <- cor.test(y[i,],y[j,],method='kendall') a<-table.element(a,round(rk$estimate,4)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-value',header=T) a<-table.element(a,paste('(',round(rp$p.value,4),')',sep='')) a<-table.element(a,paste('(',round(rs$p.value,4),')',sep='')) a<-table.element(a,paste('(',round(rk$p.value,4),')',sep='')) a<-table.row.end(a) } } a<-table.end(a) table.save(a,file='mytable1.tab')
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