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Type 'q()' to quit R. > source('/home/pw/wessanet/cretab') > > > > myrfcuid = 'r0661991' > > x <- array(list(11,13,11,16,15,17,14,16,15,17,10,17,11,15,16,16,17,14,14,16,13,17,18,16,11,16,15,16,12,15,19,16,13,16,15,13,13,15,10,17,12,13,15,17,18,14,15,14,11,17,14,13,9,16,13,15,13,15,16,13,16,17,13,11,12,14,11,13,15,17,13,16,13,17,15,16,14,16,14,16,13,15,11,12,14,17,17,14,15,14,15,16,18,15,15,16,18,14,16,15,12,17,14,10,14,17,12,20,13,17,14,17,15,14,14,17,15,17,14,16,17,18,8,18,15,16,15,15,14,13,17,16,14,12,12,16,13,16,13,16,16,14,12,15,14,14,14,15,14,15,17,16,11,11,15,18,15,11,17,18,12,15,15,19,10,17,17,14,16,13,15,17,16,14,16,19,15,14,17,16,14,16,12,15,15,12,16,18,13,15,14,18,13,15,14,16,12,16),dim=c(2,99),dimnames=list(c('Imago','Tevredenheid'),1:99)) > y <- array(NA,dim=c(2,99),dimnames=list(c('Imago','Tevredenheid'),1:99)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par1 = 'kendall' > main = 'Scatter Plots and p-values' > par1 <- 'kendall' > #'GNU S' R Code compiled by R2WASP v. 1.2.327 (Thu, 22 Sep 2016 20:11:42 +0200) > #Author: root > #To cite this work: Patrick Wessa, (2016), Multivariate Correlation Matrix (v1.0.11) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/Patrick.Wessa/rwasp_pairs.wasp/ > #Source of accompanying publication: > # > panel.tau <- function(x, y, digits=2, prefix='', cex.cor) + { + usr <- par('usr'); on.exit(par(usr)) + par(usr = c(0, 1, 0, 1)) + rr <- cor.test(x, y, method=par1) + r <- round(rr$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', ...) + } > x <- na.omit(x) > y <- t(na.omit(t(y))) > postscript(file="/home/pw/wessanet/rcomp/tmp/1z4bi1481127512.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main) > dev.off() null device 1 > > n <- length(y[,1]) > print(n) [1] 2 > 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$estimate,3)) + } + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/home/pw/wessanet/rcomp/tmp/2k0s01481127512.tab") > ncorrs <- (n*n -n)/2 > mycorrs <- array(0, dim=c(10,3)) > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'pair',1,TRUE) > a<-table.element(a,'Pearson r',1,TRUE) > a<-table.element(a,'Spearman rho',1,TRUE) > a<-table.element(a,'Kendall tau',1,TRUE) > a<-table.row.end(a) > cor.test(y[1,],y[2,],method=par1) Kendall's rank correlation tau data: y[1, ] and y[2, ] z = -0.07167, p-value = 0.9429 alternative hypothesis: true tau is not equal to 0 sample estimates: tau -0.005533761 > for (i in 1:(n-1)) + { + for (j in (i+1):n) + { + a<-table.row.start(a) + dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='') + a<-table.element(a,dum,header=TRUE) + rp <- cor.test(y[i,],y[j,],method='pearson') + a<-table.element(a,round(rp$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$p.value,4),')',sep='')) + a<-table.row.end(a) + for (iii in 1:10) { + iiid100 <- iii / 100 + if (rp$p.value < iiid100) mycorrs[iii, 1] = mycorrs[iii, 1] + 1 + if (rs$p.value < iiid100) mycorrs[iii, 2] = mycorrs[iii, 2] + 1 + if (rk$p.value < iiid100) mycorrs[iii, 3] = mycorrs[iii, 3] + 1 + } + } + } Warning message: In cor.test.default(y[i, ], y[j, ], method = "spearman") : Cannot compute exact p-value with ties > a<-table.end(a) > table.save(a,file="/home/pw/wessanet/rcomp/tmp/3ivsm1481127512.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Meta Analysis of Correlation Tests',4,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Number of significant by total number of Correlations',4,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Type I error',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) > for (iii in 1:10) { + iiid100 <- iii / 100 + a<-table.row.start(a) + a<-table.element(a,round(iiid100,2),header=T) + a<-table.element(a,round(mycorrs[iii,1]/ncorrs,2)) + a<-table.element(a,round(mycorrs[iii,2]/ncorrs,2)) + a<-table.element(a,round(mycorrs[iii,3]/ncorrs,2)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/home/pw/wessanet/rcomp/tmp/4y7yi1481127512.tab") > > try(system("convert /home/pw/wessanet/rcomp/tmp/1z4bi1481127512.ps /home/pw/wessanet/rcomp/tmp/1z4bi1481127512.png",intern=TRUE)) character(0) > > proc.time() user system elapsed 0.536 0.056 0.592