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Type 'q()' to quit R. > x <- array(list(16198.9,16896.2,16554.2,16698,19554.2,19691.6,15903.8,15930.7,18003.8,17444.6,18329.6,17699.4,16260.7,15189.8,14851.9,15672.7,18174.1,17180.8,18406.6,17664.9,18466.5,17862.9,16016.5,16162.3,17428.5,17463.6,17167.2,16772.1,19630,19106.9,17183.6,16721.3,18344.7,18161.3,19301.4,18509.9,18147.5,17802.7,16192.9,16409.9,18374.4,17967.7,20515.2,20286.6,18957.2,19537.3,16471.5,18021.9,18746.8,20194.3,19009.5,19049.6,19211.2,20244.7,20547.7,21473.3,19325.8,19673.6,20605.5,21053.2,20056.9,20159.5,16141.4,18203.6,20359.8,21289.5,19711.6,20432.3,15638.6,17180.4,14384.5,15816.8,13855.6,15071.8,14308.3,14521.1,15290.6,15668.8,14423.8,14346.9,13779.7,13881,15686.3,15465.9,14733.8,14238.2,12522.5,13557.7,16189.4,16127.6,16059.1,16793.9,16007.1,16014,15806.8,16867.9,15160,16014.6,15692.1,15878.6,18908.9,18664.9,16969.9,17962.5,16997.5,17332.7,19858.9,19542.1,17681.2,17203.6),dim=c(2,55),dimnames=list(c('Uitvoer','Invoer'),1:55)) > y <- array(NA,dim=c(2,55),dimnames=list(c('Uitvoer','Invoer'),1:55)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'Pearson Chi-Squared' > par2 = '2' > par1 = '1' > main = 'Association Plot' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Dr. Ian E. Holliday > #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(vcd) Loading required package: MASS Loading required package: grid Loading required package: colorspace > 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,])))) [,1] [,2] [1,] 16198.9 16896.2 [2,] 16554.2 16698.0 [3,] 19554.2 19691.6 [4,] 15903.8 15930.7 [5,] 18003.8 17444.6 [6,] 18329.6 17699.4 [7,] 16260.7 15189.8 [8,] 14851.9 15672.7 [9,] 18174.1 17180.8 [10,] 18406.6 17664.9 [11,] 18466.5 17862.9 [12,] 16016.5 16162.3 [13,] 17428.5 17463.6 [14,] 17167.2 16772.1 [15,] 19630.0 19106.9 [16,] 17183.6 16721.3 [17,] 18344.7 18161.3 [18,] 19301.4 18509.9 [19,] 18147.5 17802.7 [20,] 16192.9 16409.9 [21,] 18374.4 17967.7 [22,] 20515.2 20286.6 [23,] 18957.2 19537.3 [24,] 16471.5 18021.9 [25,] 18746.8 20194.3 [26,] 19009.5 19049.6 [27,] 19211.2 20244.7 [28,] 20547.7 21473.3 [29,] 19325.8 19673.6 [30,] 20605.5 21053.2 [31,] 20056.9 20159.5 [32,] 16141.4 18203.6 [33,] 20359.8 21289.5 [34,] 19711.6 20432.3 [35,] 15638.6 17180.4 [36,] 14384.5 15816.8 [37,] 13855.6 15071.8 [38,] 14308.3 14521.1 [39,] 15290.6 15668.8 [40,] 14423.8 14346.9 [41,] 13779.7 13881.0 [42,] 15686.3 15465.9 [43,] 14733.8 14238.2 [44,] 12522.5 13557.7 [45,] 16189.4 16127.6 [46,] 16059.1 16793.9 [47,] 16007.1 16014.0 [48,] 15806.8 16867.9 [49,] 15160.0 16014.6 [50,] 15692.1 15878.6 [51,] 18908.9 18664.9 [52,] 16969.9 17962.5 [53,] 16997.5 17332.7 [54,] 19858.9 19542.1 [55,] 17681.2 17203.6 > (table1 <- table(z[,cat1],z[,cat2])) 13557.7 13881 14238.2 14346.9 14521.1 15071.8 15189.8 15465.9 15668.8 12522.5 1 0 0 0 0 0 0 0 0 13779.7 0 1 0 0 0 0 0 0 0 13855.6 0 0 0 0 0 1 0 0 0 14308.3 0 0 0 0 1 0 0 0 0 14384.5 0 0 0 0 0 0 0 0 0 14423.8 0 0 0 1 0 0 0 0 0 14733.8 0 0 1 0 0 0 0 0 0 14851.9 0 0 0 0 0 0 0 0 0 15160 0 0 0 0 0 0 0 0 0 15290.6 0 0 0 0 0 0 0 0 1 15638.6 0 0 0 0 0 0 0 0 0 15686.3 0 0 0 0 0 0 0 1 0 15692.1 0 0 0 0 0 0 0 0 0 15806.8 0 0 0 0 0 0 0 0 0 15903.8 0 0 0 0 0 0 0 0 0 16007.1 0 0 0 0 0 0 0 0 0 16016.5 0 0 0 0 0 0 0 0 0 16059.1 0 0 0 0 0 0 0 0 0 16141.4 0 0 0 0 0 0 0 0 0 16189.4 0 0 0 0 0 0 0 0 0 16192.9 0 0 0 0 0 0 0 0 0 16198.9 0 0 0 0 0 0 0 0 0 16260.7 0 0 0 0 0 0 1 0 0 16471.5 0 0 0 0 0 0 0 0 0 16554.2 0 0 0 0 0 0 0 0 0 16969.9 0 0 0 0 0 0 0 0 0 16997.5 0 0 0 0 0 0 0 0 0 17167.2 0 0 0 0 0 0 0 0 0 17183.6 0 0 0 0 0 0 0 0 0 17428.5 0 0 0 0 0 0 0 0 0 17681.2 0 0 0 0 0 0 0 0 0 18003.8 0 0 0 0 0 0 0 0 0 18147.5 0 0 0 0 0 0 0 0 0 18174.1 0 0 0 0 0 0 0 0 0 18329.6 0 0 0 0 0 0 0 0 0 18344.7 0 0 0 0 0 0 0 0 0 18374.4 0 0 0 0 0 0 0 0 0 18406.6 0 0 0 0 0 0 0 0 0 18466.5 0 0 0 0 0 0 0 0 0 18746.8 0 0 0 0 0 0 0 0 0 18908.9 0 0 0 0 0 0 0 0 0 18957.2 0 0 0 0 0 0 0 0 0 19009.5 0 0 0 0 0 0 0 0 0 19211.2 0 0 0 0 0 0 0 0 0 19301.4 0 0 0 0 0 0 0 0 0 19325.8 0 0 0 0 0 0 0 0 0 19554.2 0 0 0 0 0 0 0 0 0 19630 0 0 0 0 0 0 0 0 0 19711.6 0 0 0 0 0 0 0 0 0 19858.9 0 0 0 0 0 0 0 0 0 20056.9 0 0 0 0 0 0 0 0 0 20359.8 0 0 0 0 0 0 0 0 0 20515.2 0 0 0 0 0 0 0 0 0 20547.7 0 0 0 0 0 0 0 0 0 20605.5 0 0 0 0 0 0 0 0 0 15672.7 15816.8 15878.6 15930.7 16014 16014.6 16127.6 16162.3 16409.9 12522.5 0 0 0 0 0 0 0 0 0 13779.7 0 0 0 0 0 0 0 0 0 13855.6 0 0 0 0 0 0 0 0 0 14308.3 0 0 0 0 0 0 0 0 0 14384.5 0 1 0 0 0 0 0 0 0 14423.8 0 0 0 0 0 0 0 0 0 14733.8 0 0 0 0 0 0 0 0 0 14851.9 1 0 0 0 0 0 0 0 0 15160 0 0 0 0 0 1 0 0 0 15290.6 0 0 0 0 0 0 0 0 0 15638.6 0 0 0 0 0 0 0 0 0 15686.3 0 0 0 0 0 0 0 0 0 15692.1 0 0 1 0 0 0 0 0 0 15806.8 0 0 0 0 0 0 0 0 0 15903.8 0 0 0 1 0 0 0 0 0 16007.1 0 0 0 0 1 0 0 0 0 16016.5 0 0 0 0 0 0 0 1 0 16059.1 0 0 0 0 0 0 0 0 0 16141.4 0 0 0 0 0 0 0 0 0 16189.4 0 0 0 0 0 0 1 0 0 16192.9 0 0 0 0 0 0 0 0 1 16198.9 0 0 0 0 0 0 0 0 0 16260.7 0 0 0 0 0 0 0 0 0 16471.5 0 0 0 0 0 0 0 0 0 16554.2 0 0 0 0 0 0 0 0 0 16969.9 0 0 0 0 0 0 0 0 0 16997.5 0 0 0 0 0 0 0 0 0 17167.2 0 0 0 0 0 0 0 0 0 17183.6 0 0 0 0 0 0 0 0 0 17428.5 0 0 0 0 0 0 0 0 0 17681.2 0 0 0 0 0 0 0 0 0 18003.8 0 0 0 0 0 0 0 0 0 18147.5 0 0 0 0 0 0 0 0 0 18174.1 0 0 0 0 0 0 0 0 0 18329.6 0 0 0 0 0 0 0 0 0 18344.7 0 0 0 0 0 0 0 0 0 18374.4 0 0 0 0 0 0 0 0 0 18406.6 0 0 0 0 0 0 0 0 0 18466.5 0 0 0 0 0 0 0 0 0 18746.8 0 0 0 0 0 0 0 0 0 18908.9 0 0 0 0 0 0 0 0 0 18957.2 0 0 0 0 0 0 0 0 0 19009.5 0 0 0 0 0 0 0 0 0 19211.2 0 0 0 0 0 0 0 0 0 19301.4 0 0 0 0 0 0 0 0 0 19325.8 0 0 0 0 0 0 0 0 0 19554.2 0 0 0 0 0 0 0 0 0 19630 0 0 0 0 0 0 0 0 0 19711.6 0 0 0 0 0 0 0 0 0 19858.9 0 0 0 0 0 0 0 0 0 20056.9 0 0 0 0 0 0 0 0 0 20359.8 0 0 0 0 0 0 0 0 0 20515.2 0 0 0 0 0 0 0 0 0 20547.7 0 0 0 0 0 0 0 0 0 20605.5 0 0 0 0 0 0 0 0 0 16698 16721.3 16772.1 16793.9 16867.9 16896.2 17180.4 17180.8 17203.6 12522.5 0 0 0 0 0 0 0 0 0 13779.7 0 0 0 0 0 0 0 0 0 13855.6 0 0 0 0 0 0 0 0 0 14308.3 0 0 0 0 0 0 0 0 0 14384.5 0 0 0 0 0 0 0 0 0 14423.8 0 0 0 0 0 0 0 0 0 14733.8 0 0 0 0 0 0 0 0 0 14851.9 0 0 0 0 0 0 0 0 0 15160 0 0 0 0 0 0 0 0 0 15290.6 0 0 0 0 0 0 0 0 0 15638.6 0 0 0 0 0 0 1 0 0 15686.3 0 0 0 0 0 0 0 0 0 15692.1 0 0 0 0 0 0 0 0 0 15806.8 0 0 0 0 1 0 0 0 0 15903.8 0 0 0 0 0 0 0 0 0 16007.1 0 0 0 0 0 0 0 0 0 16016.5 0 0 0 0 0 0 0 0 0 16059.1 0 0 0 1 0 0 0 0 0 16141.4 0 0 0 0 0 0 0 0 0 16189.4 0 0 0 0 0 0 0 0 0 16192.9 0 0 0 0 0 0 0 0 0 16198.9 0 0 0 0 0 1 0 0 0 16260.7 0 0 0 0 0 0 0 0 0 16471.5 0 0 0 0 0 0 0 0 0 16554.2 1 0 0 0 0 0 0 0 0 16969.9 0 0 0 0 0 0 0 0 0 16997.5 0 0 0 0 0 0 0 0 0 17167.2 0 0 1 0 0 0 0 0 0 17183.6 0 1 0 0 0 0 0 0 0 17428.5 0 0 0 0 0 0 0 0 0 17681.2 0 0 0 0 0 0 0 0 1 18003.8 0 0 0 0 0 0 0 0 0 18147.5 0 0 0 0 0 0 0 0 0 18174.1 0 0 0 0 0 0 0 1 0 18329.6 0 0 0 0 0 0 0 0 0 18344.7 0 0 0 0 0 0 0 0 0 18374.4 0 0 0 0 0 0 0 0 0 18406.6 0 0 0 0 0 0 0 0 0 18466.5 0 0 0 0 0 0 0 0 0 18746.8 0 0 0 0 0 0 0 0 0 18908.9 0 0 0 0 0 0 0 0 0 18957.2 0 0 0 0 0 0 0 0 0 19009.5 0 0 0 0 0 0 0 0 0 19211.2 0 0 0 0 0 0 0 0 0 19301.4 0 0 0 0 0 0 0 0 0 19325.8 0 0 0 0 0 0 0 0 0 19554.2 0 0 0 0 0 0 0 0 0 19630 0 0 0 0 0 0 0 0 0 19711.6 0 0 0 0 0 0 0 0 0 19858.9 0 0 0 0 0 0 0 0 0 20056.9 0 0 0 0 0 0 0 0 0 20359.8 0 0 0 0 0 0 0 0 0 20515.2 0 0 0 0 0 0 0 0 0 20547.7 0 0 0 0 0 0 0 0 0 20605.5 0 0 0 0 0 0 0 0 0 17332.7 17444.6 17463.6 17664.9 17699.4 17802.7 17862.9 17962.5 12522.5 0 0 0 0 0 0 0 0 13779.7 0 0 0 0 0 0 0 0 13855.6 0 0 0 0 0 0 0 0 14308.3 0 0 0 0 0 0 0 0 14384.5 0 0 0 0 0 0 0 0 14423.8 0 0 0 0 0 0 0 0 14733.8 0 0 0 0 0 0 0 0 14851.9 0 0 0 0 0 0 0 0 15160 0 0 0 0 0 0 0 0 15290.6 0 0 0 0 0 0 0 0 15638.6 0 0 0 0 0 0 0 0 15686.3 0 0 0 0 0 0 0 0 15692.1 0 0 0 0 0 0 0 0 15806.8 0 0 0 0 0 0 0 0 15903.8 0 0 0 0 0 0 0 0 16007.1 0 0 0 0 0 0 0 0 16016.5 0 0 0 0 0 0 0 0 16059.1 0 0 0 0 0 0 0 0 16141.4 0 0 0 0 0 0 0 0 16189.4 0 0 0 0 0 0 0 0 16192.9 0 0 0 0 0 0 0 0 16198.9 0 0 0 0 0 0 0 0 16260.7 0 0 0 0 0 0 0 0 16471.5 0 0 0 0 0 0 0 0 16554.2 0 0 0 0 0 0 0 0 16969.9 0 0 0 0 0 0 0 1 16997.5 1 0 0 0 0 0 0 0 17167.2 0 0 0 0 0 0 0 0 17183.6 0 0 0 0 0 0 0 0 17428.5 0 0 1 0 0 0 0 0 17681.2 0 0 0 0 0 0 0 0 18003.8 0 1 0 0 0 0 0 0 18147.5 0 0 0 0 0 1 0 0 18174.1 0 0 0 0 0 0 0 0 18329.6 0 0 0 0 1 0 0 0 18344.7 0 0 0 0 0 0 0 0 18374.4 0 0 0 0 0 0 0 0 18406.6 0 0 0 1 0 0 0 0 18466.5 0 0 0 0 0 0 1 0 18746.8 0 0 0 0 0 0 0 0 18908.9 0 0 0 0 0 0 0 0 18957.2 0 0 0 0 0 0 0 0 19009.5 0 0 0 0 0 0 0 0 19211.2 0 0 0 0 0 0 0 0 19301.4 0 0 0 0 0 0 0 0 19325.8 0 0 0 0 0 0 0 0 19554.2 0 0 0 0 0 0 0 0 19630 0 0 0 0 0 0 0 0 19711.6 0 0 0 0 0 0 0 0 19858.9 0 0 0 0 0 0 0 0 20056.9 0 0 0 0 0 0 0 0 20359.8 0 0 0 0 0 0 0 0 20515.2 0 0 0 0 0 0 0 0 20547.7 0 0 0 0 0 0 0 0 20605.5 0 0 0 0 0 0 0 0 17967.7 18021.9 18161.3 18203.6 18509.9 18664.9 19049.6 19106.9 12522.5 0 0 0 0 0 0 0 0 13779.7 0 0 0 0 0 0 0 0 13855.6 0 0 0 0 0 0 0 0 14308.3 0 0 0 0 0 0 0 0 14384.5 0 0 0 0 0 0 0 0 14423.8 0 0 0 0 0 0 0 0 14733.8 0 0 0 0 0 0 0 0 14851.9 0 0 0 0 0 0 0 0 15160 0 0 0 0 0 0 0 0 15290.6 0 0 0 0 0 0 0 0 15638.6 0 0 0 0 0 0 0 0 15686.3 0 0 0 0 0 0 0 0 15692.1 0 0 0 0 0 0 0 0 15806.8 0 0 0 0 0 0 0 0 15903.8 0 0 0 0 0 0 0 0 16007.1 0 0 0 0 0 0 0 0 16016.5 0 0 0 0 0 0 0 0 16059.1 0 0 0 0 0 0 0 0 16141.4 0 0 0 1 0 0 0 0 16189.4 0 0 0 0 0 0 0 0 16192.9 0 0 0 0 0 0 0 0 16198.9 0 0 0 0 0 0 0 0 16260.7 0 0 0 0 0 0 0 0 16471.5 0 1 0 0 0 0 0 0 16554.2 0 0 0 0 0 0 0 0 16969.9 0 0 0 0 0 0 0 0 16997.5 0 0 0 0 0 0 0 0 17167.2 0 0 0 0 0 0 0 0 17183.6 0 0 0 0 0 0 0 0 17428.5 0 0 0 0 0 0 0 0 17681.2 0 0 0 0 0 0 0 0 18003.8 0 0 0 0 0 0 0 0 18147.5 0 0 0 0 0 0 0 0 18174.1 0 0 0 0 0 0 0 0 18329.6 0 0 0 0 0 0 0 0 18344.7 0 0 1 0 0 0 0 0 18374.4 1 0 0 0 0 0 0 0 18406.6 0 0 0 0 0 0 0 0 18466.5 0 0 0 0 0 0 0 0 18746.8 0 0 0 0 0 0 0 0 18908.9 0 0 0 0 0 1 0 0 18957.2 0 0 0 0 0 0 0 0 19009.5 0 0 0 0 0 0 1 0 19211.2 0 0 0 0 0 0 0 0 19301.4 0 0 0 0 1 0 0 0 19325.8 0 0 0 0 0 0 0 0 19554.2 0 0 0 0 0 0 0 0 19630 0 0 0 0 0 0 0 1 19711.6 0 0 0 0 0 0 0 0 19858.9 0 0 0 0 0 0 0 0 20056.9 0 0 0 0 0 0 0 0 20359.8 0 0 0 0 0 0 0 0 20515.2 0 0 0 0 0 0 0 0 20547.7 0 0 0 0 0 0 0 0 20605.5 0 0 0 0 0 0 0 0 19537.3 19542.1 19673.6 19691.6 20159.5 20194.3 20244.7 20286.6 12522.5 0 0 0 0 0 0 0 0 13779.7 0 0 0 0 0 0 0 0 13855.6 0 0 0 0 0 0 0 0 14308.3 0 0 0 0 0 0 0 0 14384.5 0 0 0 0 0 0 0 0 14423.8 0 0 0 0 0 0 0 0 14733.8 0 0 0 0 0 0 0 0 14851.9 0 0 0 0 0 0 0 0 15160 0 0 0 0 0 0 0 0 15290.6 0 0 0 0 0 0 0 0 15638.6 0 0 0 0 0 0 0 0 15686.3 0 0 0 0 0 0 0 0 15692.1 0 0 0 0 0 0 0 0 15806.8 0 0 0 0 0 0 0 0 15903.8 0 0 0 0 0 0 0 0 16007.1 0 0 0 0 0 0 0 0 16016.5 0 0 0 0 0 0 0 0 16059.1 0 0 0 0 0 0 0 0 16141.4 0 0 0 0 0 0 0 0 16189.4 0 0 0 0 0 0 0 0 16192.9 0 0 0 0 0 0 0 0 16198.9 0 0 0 0 0 0 0 0 16260.7 0 0 0 0 0 0 0 0 16471.5 0 0 0 0 0 0 0 0 16554.2 0 0 0 0 0 0 0 0 16969.9 0 0 0 0 0 0 0 0 16997.5 0 0 0 0 0 0 0 0 17167.2 0 0 0 0 0 0 0 0 17183.6 0 0 0 0 0 0 0 0 17428.5 0 0 0 0 0 0 0 0 17681.2 0 0 0 0 0 0 0 0 18003.8 0 0 0 0 0 0 0 0 18147.5 0 0 0 0 0 0 0 0 18174.1 0 0 0 0 0 0 0 0 18329.6 0 0 0 0 0 0 0 0 18344.7 0 0 0 0 0 0 0 0 18374.4 0 0 0 0 0 0 0 0 18406.6 0 0 0 0 0 0 0 0 18466.5 0 0 0 0 0 0 0 0 18746.8 0 0 0 0 0 1 0 0 18908.9 0 0 0 0 0 0 0 0 18957.2 1 0 0 0 0 0 0 0 19009.5 0 0 0 0 0 0 0 0 19211.2 0 0 0 0 0 0 1 0 19301.4 0 0 0 0 0 0 0 0 19325.8 0 0 1 0 0 0 0 0 19554.2 0 0 0 1 0 0 0 0 19630 0 0 0 0 0 0 0 0 19711.6 0 0 0 0 0 0 0 0 19858.9 0 1 0 0 0 0 0 0 20056.9 0 0 0 0 1 0 0 0 20359.8 0 0 0 0 0 0 0 0 20515.2 0 0 0 0 0 0 0 1 20547.7 0 0 0 0 0 0 0 0 20605.5 0 0 0 0 0 0 0 0 20432.3 21053.2 21289.5 21473.3 12522.5 0 0 0 0 13779.7 0 0 0 0 13855.6 0 0 0 0 14308.3 0 0 0 0 14384.5 0 0 0 0 14423.8 0 0 0 0 14733.8 0 0 0 0 14851.9 0 0 0 0 15160 0 0 0 0 15290.6 0 0 0 0 15638.6 0 0 0 0 15686.3 0 0 0 0 15692.1 0 0 0 0 15806.8 0 0 0 0 15903.8 0 0 0 0 16007.1 0 0 0 0 16016.5 0 0 0 0 16059.1 0 0 0 0 16141.4 0 0 0 0 16189.4 0 0 0 0 16192.9 0 0 0 0 16198.9 0 0 0 0 16260.7 0 0 0 0 16471.5 0 0 0 0 16554.2 0 0 0 0 16969.9 0 0 0 0 16997.5 0 0 0 0 17167.2 0 0 0 0 17183.6 0 0 0 0 17428.5 0 0 0 0 17681.2 0 0 0 0 18003.8 0 0 0 0 18147.5 0 0 0 0 18174.1 0 0 0 0 18329.6 0 0 0 0 18344.7 0 0 0 0 18374.4 0 0 0 0 18406.6 0 0 0 0 18466.5 0 0 0 0 18746.8 0 0 0 0 18908.9 0 0 0 0 18957.2 0 0 0 0 19009.5 0 0 0 0 19211.2 0 0 0 0 19301.4 0 0 0 0 19325.8 0 0 0 0 19554.2 0 0 0 0 19630 0 0 0 0 19711.6 1 0 0 0 19858.9 0 0 0 0 20056.9 0 0 0 0 20359.8 0 0 1 0 20515.2 0 0 0 0 20547.7 0 0 0 1 20605.5 0 1 0 0 > (V1<-dimnames(y)[[1]][cat1]) [1] "Uitvoer" > (V2<-dimnames(y)[[1]][cat2]) [1] "Invoer" > postscript(file="/var/www/html/rcomp/tmp/1d7rg1292676384.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > assoc(ftable(z[,cat1],z[,cat2],row.vars=1,dnn=c(V1,V2)),shade=T) > dev.off() null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/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="/var/www/html/rcomp/tmp/2gqp41292676384.tab") > (cst<-chisq.test(table1, simulate.p.value=simulate.p.value) ) Pearson's Chi-squared test data: table1 X-squared = 2970, df = 2916, p-value = 0.2384 Warning message: In chisq.test(table1, simulate.p.value = simulate.p.value) : Chi-squared approximation may be incorrect > if (par3 == 'McNemar Chi-Squared') { + (cst <- mcnemar.test(table1)) + } > if (par3 != 'McNemar Chi-Squared') { + 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="/var/www/html/rcomp/tmp/3j8o91292676384.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$method, 2,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Chi Square Statistic', 1, TRUE) > a<-table.element(a, round(cst$statistic, digits=2), 1,FALSE) > a<-table.row.end(a) > if(!simulate.p.value){ + 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="/var/www/html/rcomp/tmp/4nr4f1292676384.tab") > > try(system("convert tmp/1d7rg1292676384.ps tmp/1d7rg1292676384.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 32.043 0.700 73.505