R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- array(list(3,36,1,36,3,56,3,48,3,32,1,44,2,39,3,34,3,41,2,50,1,39,1,62,3,52,3,37,3,50,1,41,3,55,3,41,3,56,2,39,2,52,1,46,1,44,3,48,3,41,1,50,1,50,3,44,1,52,2,54,3,44,2,52,2,37,3,52,1,50,3,36,3,50,1,52,2,55,1,31,1,36,2,49,1,42,1,37,3,41,2,30,2,52,1,30,1,41,1,44,1,66,2,48,3,43,3,57,3,46,3,54,2,48,2,48,2,52,3,62,3,58,2,58,2,62,2,48,3,46,2,34,3,66,3,52,2,55,2,55,3,57,3,56,2,55,1,56,2,54,2,55,2,46,2,52,3,32,2,44,3,46,1,59,3,46,3,46,1,54,1,66,2,56,1,59,3,57,1,52,3,48,2,44,3,41,1,50,1,48,2,48,3,59,1,34,3,46,1,54,2,55,2,54,3,59,3,44,1,54,3,52,3,66,3,44,2,57,3,39,3,60,3,45,3,41,1,50,3,39,1,43,3,48,3,37,3,58,2,46,3,43,2,44,3,34,2,30,2,50,2,39,3,37,3,55,1,48,1,41,3,39,3,36,2,43,1,50,3,55,3,43,3,60,2,48,1,30,3,43,3,39,3,52,2,39,3,39,2,56,3,59,3,46,2,57,3,50,3,54,3,50,3,60,1,59,3,41,2,48,3,59,3,60,1,56,1,56,3,51),dim=c(2,160),dimnames=list(c('MOMAGE','MC30VRB'),1:160))
>  y <- array(NA,dim=c(2,160),dimnames=list(c('MOMAGE','MC30VRB'),1:160))
>  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'
> 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       0.7000       0.9000  
Treatment39  Treatment41  Treatment42  Treatment43  Treatment44  Treatment45  
     0.9000       0.9000      -0.5000       1.0000       0.6000       1.5000  
Treatment46  Treatment48  Treatment49  Treatment50  Treatment51  Treatment52  
     1.1000       0.6538       0.5000       0.3333       1.5000       0.6538  
Treatment54  Treatment55  Treatment56  Treatment57  Treatment58  Treatment59  
     0.3750       0.8333       0.5000       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   17.89991  90.00009
Deg. of Freedom        26       133

Residual standard error: 0.8226132
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   17.9 0.68846  1.0174 0.4503
Residuals 133   90.0 0.67669               
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/1vpve1384178678.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/fisher/rcomp/tmp/2qzko1384178678.tab") 
> postscript(file="/var/fisher/rcomp/tmp/3jrrd1384178678.ps",horizontal=F,onefile=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/fisher/rcomp/tmp/407np1384178678.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
+ plot(thsd)
+ dev.off()
+ }
null device 
          1 
> if(intercept==TRUE){
+ 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/fisher/rcomp/tmp/5rabr1384178678.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/fisher/rcomp/tmp/6hg6g1384178678.tab") 
+ }
> library(car)
Loading required package: MASS
Loading required package: nnet
> lt.lmxdf<-levene.test(lmxdf)
Warning message:
'levene.test' is deprecated.
Use 'leveneTest' instead.
See help("Deprecated") and help("car-deprecated"). 
> 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/fisher/rcomp/tmp/7hlhg1384178678.tab") 
> 
> try(system("convert tmp/3jrrd1384178678.ps tmp/3jrrd1384178678.png",intern=TRUE))
character(0)
> try(system("convert tmp/407np1384178678.ps tmp/407np1384178678.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  5.161   0.431   5.574