R version 2.10.0 (2009-10-26)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- array(list(1,36,3,56,3,48,3,32,1,44,2,39,3,34,3,41,2,50,1,39,1,62,3,52,3,37,3,50,1,41,3,55,3,41,3,56,2,39,2,52,1,46,1,44,3,41,1,50,1,50,3,44,1,52,2,54,3,44,2,52,2,37,3,52,1,50,3,36,3,50,1,52,2,55,1,31,1,36,2,49,1,42,1,37,3,41,2,30,2,52,1,30,1,44,1,66,2,48,3,43,3,57,3,46,3,54,2,48,2,48,3,62,3,58,2,58,2,62,3,46,2,34,3,66,3,52,2,55,2,55,3,57,3,56,2,55,1,56,2,54,2,55,2,46,2,52,3,32,2,44,3,46,1,59,3,46,3,46,1,54,1,66,2,56,1,59,3,57,1,52,3,48,2,44,3,41,1,50,1,48,2,48,3,59,1,34,3,46,1,54,2,55,2,54,3,59,3,44,1,54,3,52,3,66,3,44,2,57,3,39,3,60,3,45,3,41,1,50,3,39,1,43,3,48,3,37,3,58,2,46,3,43,2,44,3,34,2,30,2,50,2,39,3,37,3,55,1,41,3,39,3,36,2,43,1,50,3,55,3,43,3,60,2,48,1,30,3,43,3,39,3,52,2,39,3,39,2,56,3,59,3,46,2,57,3,50,3,54,3,50,3,60,1,59,3,41,2,48,3,59,3,60,1,56,3,51),dim=c(2,153),dimnames=list(c('MOMAGE','MC30VRB'),1:153))
>  y <- array(NA,dim=c(2,153),dimnames=list(c('MOMAGE','MC30VRB'),1:153))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par3 = 'TRUE'
> par2 = '2'
> par1 = '1'
> ylab = 'Y Variable Name'
> xlab = 'X Variable Name'
> main = 'Title Goes Here'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Dr. Ian E. Holliday
> #To cite this work: Ian E. Holliday, 2009, STARS Bullying Study (v1.0.1) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/Ian.Holliday/rwasp_STARS_Bullying_Study_alt.wasp/
> #Source of accompanying publication: 
> #Technical description: 
> cat1 <- as.numeric(par1) #
> cat2<- as.numeric(par2) #
> intercept<-as.logical(par3)
> x <- t(x)
> x1<-as.numeric(x[,cat1])
> f1<-as.character(x[,cat2])
> xdf<-data.frame(x1,f1)
> (V1<-dimnames(y)[[1]][cat1])
[1] "MOMAGE"
> (V2<-dimnames(y)[[1]][cat2])
[1] "MC30VRB"
> names(xdf)<-c('Response', 'Treatment')
> if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, data = xdf) )

Call:
lm(formula = Response ~ Treatment, data = xdf)

Coefficients:
(Intercept)  Treatment31  Treatment32  Treatment34  Treatment36  Treatment37  
     1.5000      -0.5000       1.5000       0.7500       0.5000       0.9000  
Treatment39  Treatment41  Treatment42  Treatment43  Treatment44  Treatment45  
     0.9000       1.0556      -0.5000       1.0000       0.6000       1.5000  
Treatment46  Treatment48  Treatment49  Treatment50  Treatment51  Treatment52  
     1.1000       0.7000       0.5000       0.3333       1.5000       0.6667  
Treatment54  Treatment55  Treatment56  Treatment57  Treatment58  Treatment59  
     0.3750       0.8333       0.6429       1.1000       1.1667       0.6429  
Treatment60  Treatment62  Treatment66  
     1.5000       0.5000       0.5000  

> (aov.xdf<-aov(lmxdf) )
Call:
   aov(formula = lmxdf)

Terms:
                Treatment Residuals
Sum of Squares   18.29078  83.76151
Deg. of Freedom        26       126

Residual standard error: 0.8153367 
Estimated effects may be unbalanced
> (anova.xdf<-anova(lmxdf) )
Analysis of Variance Table

Response: Response
           Df Sum Sq Mean Sq F value Pr(>F)
Treatment  26 18.291 0.70349  1.0582 0.4001
Residuals 126 83.762 0.66477               
> 
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'ANOVA Model', length(lmxdf$coefficients)+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, paste(V1, ' ~ ', V2), length(lmxdf$coefficients)+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'means',,TRUE)
> for(i in 1:length(lmxdf$coefficients)){
+ a<-table.element(a, round(lmxdf$coefficients[i], digits=3),,FALSE)
+ }
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/15n601260445905.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, ' ',,TRUE)
> a<-table.element(a, 'Df',,FALSE)
> a<-table.element(a, 'Sum Sq',,FALSE)
> a<-table.element(a, 'Mean Sq',,FALSE)
> a<-table.element(a, 'F value',,FALSE)
> a<-table.element(a, 'Pr(>F)',,FALSE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, V2,,TRUE)
> a<-table.element(a, anova.xdf$Df[1],,FALSE)
> a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3),,FALSE)
> a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3),,FALSE)
> a<-table.element(a, round(anova.xdf$'F value'[1], digits=3),,FALSE)
> a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3),,FALSE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residuals',,TRUE)
> a<-table.element(a, anova.xdf$Df[2],,FALSE)
> a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3),,FALSE)
> a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3),,FALSE)
> a<-table.element(a, ' ',,FALSE)
> a<-table.element(a, ' ',,FALSE)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/2f8wt1260445905.tab") 
> postscript(file="/var/www/rcomp/tmp/3b78g1260445905.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> boxplot(Response ~ Treatment, data=xdf, xlab=V2, ylab=V1)
> dev.off()
null device 
          1 
> if(intercept==TRUE){
+ thsd<-TukeyHSD(aov.xdf)
+ postscript(file="/var/www/rcomp/tmp/4p6ev1260445905.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
+ plot(thsd)
+ dev.off()
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Tukey Honest Significant Difference Comparisons', 5,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a, ' ', 1, TRUE)
+ for(i in 1:4){
+ a<-table.element(a,colnames(thsd[[1]])[i], 1, TRUE)
+ }
+ a<-table.row.end(a)
+ for(i in 1:length(rownames(thsd[[1]]))){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(thsd[[1]])[i], 1, TRUE)
+ for(j in 1:4){
+ a<-table.element(a,round(thsd[[1]][i,j], digits=3), 1, FALSE)
+ }
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/56f091260445905.tab") 
+ }
> if(intercept==FALSE){
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'TukeyHSD Message', 1,TRUE)
+ a<-table.row.end(a)
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Must Include Intercept to use Tukey Test ', 1, FALSE)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/6v8mq1260445905.tab") 
+ }
> library(car)
> lt.lmxdf<-levene.test(lmxdf)
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Levenes Test for Homogeneity of Variance', 4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,' ', 1, TRUE)
> for (i in 1:3){
+ a<-table.element(a,names(lt.lmxdf)[i], 1, FALSE)
+ }
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Group', 1, TRUE)
> for (i in 1:3){
+ a<-table.element(a,round(lt.lmxdf[[i]][1], digits=3), 1, FALSE)
+ }
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,' ', 1, TRUE)
> a<-table.element(a,lt.lmxdf[[1]][2], 1, FALSE)
> a<-table.element(a,' ', 1, FALSE)
> a<-table.element(a,' ', 1, FALSE)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/7sra21260445905.tab") 
> 
> system("convert tmp/3b78g1260445905.ps tmp/3b78g1260445905.png")
> system("convert tmp/4p6ev1260445905.ps tmp/4p6ev1260445905.png")
> 
> 
> proc.time()
   user  system elapsed 
   3.16    0.75    3.79