R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- array(list(6.3
+ ,2
+ ,4.5
+ ,1
+ ,6.6
+ ,42
+ ,3
+ ,1
+ ,3
+ ,2.1
+ ,1.8
+ ,69
+ ,2547
+ ,4603
+ ,624
+ ,3
+ ,5
+ ,4
+ ,9.1
+ ,0.7
+ ,27
+ ,10.55
+ ,179.5
+ ,180
+ ,4
+ ,4
+ ,4
+ ,15.8
+ ,3.9
+ ,19
+ ,0.023
+ ,0.3
+ ,35
+ ,1
+ ,1
+ ,1
+ ,5.2
+ ,1
+ ,30.4
+ ,160
+ ,169
+ ,392
+ ,4
+ ,5
+ ,4
+ ,10.9
+ ,3.6
+ ,28
+ ,3.3
+ ,25.6
+ ,63
+ ,1
+ ,2
+ ,1
+ ,8.3
+ ,1.4
+ ,50
+ ,52.16
+ ,440
+ ,230
+ ,1
+ ,1
+ ,1
+ ,11
+ ,1.5
+ ,7
+ ,0.425
+ ,6.4
+ ,112
+ ,5
+ ,4
+ ,4
+ ,3.2
+ ,0.7
+ ,30
+ ,465
+ ,423
+ ,281
+ ,5
+ ,5
+ ,5
+ ,6.3
+ ,2.1
+ ,3.5
+ ,0.075
+ ,1.2
+ ,42
+ ,1
+ ,1
+ ,1
+ ,8.6
+ ,0
+ ,50
+ ,3
+ ,25
+ ,28
+ ,2
+ ,2
+ ,2
+ ,6.6
+ ,4.1
+ ,6
+ ,0.785
+ ,3.5
+ ,42
+ ,2
+ ,2
+ ,2
+ ,9.5
+ ,1.2
+ ,10.4
+ ,0.2
+ ,5
+ ,120
+ ,2
+ ,2
+ ,2
+ ,3.3
+ ,0.5
+ ,20
+ ,27.66
+ ,115
+ ,148
+ ,5
+ ,5
+ ,5
+ ,11
+ ,3.4
+ ,3.9
+ ,0.12
+ ,1
+ ,16
+ ,3
+ ,1
+ ,2
+ ,4.7
+ ,1.5
+ ,41
+ ,85
+ ,325
+ ,310
+ ,1
+ ,3
+ ,1
+ ,10.4
+ ,3.4
+ ,9
+ ,0.101
+ ,4
+ ,28
+ ,5
+ ,1
+ ,3
+ ,7.4
+ ,0.8
+ ,7.6
+ ,1.04
+ ,5.5
+ ,68
+ ,5
+ ,3
+ ,4
+ ,2.1
+ ,0.8
+ ,46
+ ,521
+ ,655
+ ,336
+ ,5
+ ,5
+ ,5
+ ,7.7
+ ,1.4
+ ,2.6
+ ,0.005
+ ,0.14
+ ,21.5
+ ,5
+ ,2
+ ,4
+ ,17.9
+ ,2
+ ,24
+ ,0.01
+ ,0.25
+ ,50
+ ,1
+ ,1
+ ,1
+ ,6.1
+ ,1.9
+ ,100
+ ,62
+ ,1320
+ ,267
+ ,1
+ ,1
+ ,1
+ ,11.9
+ ,1.3
+ ,3.2
+ ,0.023
+ ,0.4
+ ,19
+ ,4
+ ,1
+ ,3
+ ,10.8
+ ,2
+ ,2
+ ,0.048
+ ,0.33
+ ,30
+ ,4
+ ,1
+ ,3
+ ,13.8
+ ,5.6
+ ,5
+ ,1.7
+ ,6.3
+ ,12
+ ,2
+ ,1
+ ,1
+ ,14.3
+ ,3.1
+ ,6.5
+ ,3.5
+ ,10.8
+ ,120
+ ,2
+ ,1
+ ,1
+ ,15.2
+ ,1.8
+ ,12
+ ,0.48
+ ,15.5
+ ,140
+ ,2
+ ,2
+ ,2
+ ,10
+ ,0.9
+ ,20.2
+ ,10
+ ,115
+ ,170
+ ,4
+ ,4
+ ,4
+ ,11.9
+ ,1.8
+ ,13
+ ,1.62
+ ,11.4
+ ,17
+ ,2
+ ,1
+ ,2
+ ,6.5
+ ,1.9
+ ,27
+ ,192
+ ,180
+ ,115
+ ,4
+ ,4
+ ,4
+ ,7.5
+ ,0.9
+ ,18
+ ,2.5
+ ,12.1
+ ,31
+ ,5
+ ,5
+ ,5
+ ,10.6
+ ,2.6
+ ,4.7
+ ,0.28
+ ,1.9
+ ,21
+ ,3
+ ,1
+ ,3
+ ,7.4
+ ,2.4
+ ,9.8
+ ,4.235
+ ,50.4
+ ,52
+ ,1
+ ,1
+ ,1
+ ,8.4
+ ,1.2
+ ,29
+ ,6.8
+ ,179
+ ,164
+ ,2
+ ,3
+ ,2
+ ,5.7
+ ,0.9
+ ,7
+ ,0.75
+ ,12.3
+ ,225
+ ,2
+ ,2
+ ,2
+ ,4.9
+ ,0.5
+ ,6
+ ,3.6
+ ,21
+ ,225
+ ,3
+ ,2
+ ,3
+ ,3.2
+ ,0.6
+ ,20
+ ,55.5
+ ,175
+ ,151
+ ,5
+ ,5
+ ,5
+ ,11
+ ,2.3
+ ,4.5
+ ,0.9
+ ,2.6
+ ,60
+ ,2
+ ,1
+ ,2
+ ,4.9
+ ,0.5
+ ,7.5
+ ,2
+ ,12.3
+ ,200
+ ,3
+ ,1
+ ,3
+ ,13.2
+ ,2.6
+ ,2.3
+ ,0.104
+ ,2.5
+ ,46
+ ,3
+ ,2
+ ,2
+ ,9.7
+ ,0.6
+ ,24
+ ,4.19
+ ,58
+ ,210
+ ,4
+ ,3
+ ,4
+ ,12.8
+ ,6.6
+ ,3
+ ,3.5
+ ,3.9
+ ,14
+ ,2
+ ,1
+ ,1)
+ ,dim=c(9
+ ,42)
+ ,dimnames=list(c('SWS'
+ ,'PS'
+ ,'LifeSpan'
+ ,'BodyW'
+ ,'BrainW'
+ ,'GT'
+ ,'PI'
+ ,'SEI'
+ ,'ODI')
+ ,1:42))
>  y <- array(NA,dim=c(9,42),dimnames=list(c('SWS','PS','LifeSpan','BodyW','BrainW','GT','PI','SEI','ODI'),1:42))
>  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 = '9'
> par1 = '2'
> 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]  [,3]     [,4]    [,5]  [,6] [,7] [,8] [,9]
 [1,]  6.3  2.0   4.5    1.000    6.60  42.0    3    1    3
 [2,]  2.1  1.8  69.0 2547.000 4603.00 624.0    3    5    4
 [3,]  9.1  0.7  27.0   10.550  179.50 180.0    4    4    4
 [4,] 15.8  3.9  19.0    0.023    0.30  35.0    1    1    1
 [5,]  5.2  1.0  30.4  160.000  169.00 392.0    4    5    4
 [6,] 10.9  3.6  28.0    3.300   25.60  63.0    1    2    1
 [7,]  8.3  1.4  50.0   52.160  440.00 230.0    1    1    1
 [8,] 11.0  1.5   7.0    0.425    6.40 112.0    5    4    4
 [9,]  3.2  0.7  30.0  465.000  423.00 281.0    5    5    5
[10,]  6.3  2.1   3.5    0.075    1.20  42.0    1    1    1
[11,]  8.6  0.0  50.0    3.000   25.00  28.0    2    2    2
[12,]  6.6  4.1   6.0    0.785    3.50  42.0    2    2    2
[13,]  9.5  1.2  10.4    0.200    5.00 120.0    2    2    2
[14,]  3.3  0.5  20.0   27.660  115.00 148.0    5    5    5
[15,] 11.0  3.4   3.9    0.120    1.00  16.0    3    1    2
[16,]  4.7  1.5  41.0   85.000  325.00 310.0    1    3    1
[17,] 10.4  3.4   9.0    0.101    4.00  28.0    5    1    3
[18,]  7.4  0.8   7.6    1.040    5.50  68.0    5    3    4
[19,]  2.1  0.8  46.0  521.000  655.00 336.0    5    5    5
[20,]  7.7  1.4   2.6    0.005    0.14  21.5    5    2    4
[21,] 17.9  2.0  24.0    0.010    0.25  50.0    1    1    1
[22,]  6.1  1.9 100.0   62.000 1320.00 267.0    1    1    1
[23,] 11.9  1.3   3.2    0.023    0.40  19.0    4    1    3
[24,] 10.8  2.0   2.0    0.048    0.33  30.0    4    1    3
[25,] 13.8  5.6   5.0    1.700    6.30  12.0    2    1    1
[26,] 14.3  3.1   6.5    3.500   10.80 120.0    2    1    1
[27,] 15.2  1.8  12.0    0.480   15.50 140.0    2    2    2
[28,] 10.0  0.9  20.2   10.000  115.00 170.0    4    4    4
[29,] 11.9  1.8  13.0    1.620   11.40  17.0    2    1    2
[30,]  6.5  1.9  27.0  192.000  180.00 115.0    4    4    4
[31,]  7.5  0.9  18.0    2.500   12.10  31.0    5    5    5
[32,] 10.6  2.6   4.7    0.280    1.90  21.0    3    1    3
[33,]  7.4  2.4   9.8    4.235   50.40  52.0    1    1    1
[34,]  8.4  1.2  29.0    6.800  179.00 164.0    2    3    2
[35,]  5.7  0.9   7.0    0.750   12.30 225.0    2    2    2
[36,]  4.9  0.5   6.0    3.600   21.00 225.0    3    2    3
[37,]  3.2  0.6  20.0   55.500  175.00 151.0    5    5    5
[38,] 11.0  2.3   4.5    0.900    2.60  60.0    2    1    2
[39,]  4.9  0.5   7.5    2.000   12.30 200.0    3    1    3
[40,] 13.2  2.6   2.3    0.104    2.50  46.0    3    2    2
[41,]  9.7  0.6  24.0    4.190   58.00 210.0    4    3    4
[42,] 12.8  6.6   3.0    3.500    3.90  14.0    2    1    1
> (table1 <- table(z[,cat1],z[,cat2]))
     
      1 2 3 4 5
  0   0 1 0 0 0
  0.5 0 0 2 0 1
  0.6 0 0 0 1 1
  0.7 0 0 0 1 1
  0.8 0 0 0 1 1
  0.9 0 1 0 1 1
  1   0 0 0 1 0
  1.2 0 2 0 0 0
  1.3 0 0 1 0 0
  1.4 1 0 0 1 0
  1.5 1 0 0 1 0
  1.8 0 2 0 1 0
  1.9 1 0 0 1 0
  2   1 0 2 0 0
  2.1 1 0 0 0 0
  2.3 0 1 0 0 0
  2.4 1 0 0 0 0
  2.6 0 1 1 0 0
  3.1 1 0 0 0 0
  3.4 0 1 1 0 0
  3.6 1 0 0 0 0
  3.9 1 0 0 0 0
  4.1 0 1 0 0 0
  5.6 1 0 0 0 0
  6.6 1 0 0 0 0
> (V1<-dimnames(y)[[1]][cat1])
[1] "PS"
> (V2<-dimnames(y)[[1]][cat2])
[1] "ODI"
> postscript(file="/var/www/html/rcomp/tmp/1ebhu1292316011.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/2ibyi1292316011.tab") 
> (cst<-chisq.test(table1, simulate.p.value=simulate.p.value) )

	Pearson's Chi-squared test

data:  table1 
X-squared = 91.9051, df = 96, p-value = 0.5993

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$expected[nr, nc], digits=2), 1, FALSE)
+ }
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/33ten1292316011.tab") 
+ }
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Statistical Results',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, cst$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/46cvb1292316011.tab") 
> 
> try(system("convert tmp/1ebhu1292316011.ps tmp/1ebhu1292316011.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.767   0.243   5.718