R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- array(list(1,86,3,86,3,103,3,74,1,63,2,82,3,93,3,77,2,111,1,71,1,103,3,89,3,75,3,88,1,84,3,85,3,70,3,104,2,88,2,77,1,77,1,72,3,83,1,110,1,91,3,80,1,91,2,86,3,85,2,107,2,93,3,87,1,84,3,73,3,84,1,86,2,99,1,75,1,87,2,79,1,82,1,95,3,84,2,85,2,95,1,63,1,85,1,86,2,75,3,98,3,71,3,63,3,71,2,84,2,81,3,79,3,63,2,93,2,92,3,83,2,80,3,111,3,92,2,79,2,69,3,83,3,80,2,91,1,97,2,85,2,85,2,99,2,67,3,87,2,68,3,81,1,80,3,93,3,93,1,102,1,104,2,90,1,85,3,92,1,82,3,85,2,89,3,77,1,79,1,76,2,101,3,81,3,89,1,81,2,77,2,95,3,85,3,81,1,76,3,93,3,104,3,89,2,76,3,77,3,71,3,79,3,89,1,81,3,99,1,81,3,84,3,85,3,111,2,78,3,111,2,78,3,87,2,92,2,93,2,70,3,84,3,75,3,85,3,87,2,75,1,103,3,86,3,77,3,74,2,74,1,76,3,83,3,101,3,83,2,92,3,74,2,87,3,71,3,79,2,83,3,80,3,90,3,80,3,96,1,109,3,98,2,85,3,83,3,86,1,72,3,75),dim=c(2,151),dimnames=list(c('MOMAGEMVRBIQ0',''),1:151))
>  y <- array(NA,dim=c(2,151),dimnames=list(c('MOMAGEMVRBIQ0',''),1:151))
>  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] "MOMAGEMVRBIQ0"
> (V2<-dimnames(y)[[1]][cat2])
[1] ""
> 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)  Treatment102  Treatment103  Treatment104  Treatment107  
   2.500e+00    -1.500e+00    -8.333e-01    -1.667e-01    -5.000e-01  
Treatment109  Treatment110  Treatment111   Treatment63   Treatment67  
  -1.500e+00    -1.500e+00     2.500e-01    -5.000e-01    -5.000e-01  
 Treatment68   Treatment69   Treatment70   Treatment71   Treatment72  
  -5.000e-01    -5.000e-01     1.078e-15     1.000e-01    -1.500e+00  
 Treatment73   Treatment74   Treatment75   Treatment76   Treatment77  
   5.000e-01     2.500e-01    -1.667e-01    -1.250e+00    -7.143e-02  
 Treatment78   Treatment79   Treatment80   Treatment81   Treatment82  
  -5.000e-01    -1.667e-01     1.081e-15    -5.000e-01    -1.167e+00  
 Treatment83   Treatment84   Treatment85   Treatment86   Treatment87  
   3.571e-01    -2.143e-01    -1.667e-01    -5.000e-01     1.069e-15  
 Treatment88   Treatment89   Treatment90   Treatment91   Treatment92  
   1.305e-15     3.000e-01     1.135e-15    -1.167e+00    -1.000e-01  
 Treatment93   Treatment95   Treatment96   Treatment97   Treatment98  
   7.143e-02    -8.333e-01     5.000e-01    -1.500e+00     5.000e-01  
 Treatment99  
  -1.667e-01  

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

Terms:
                Treatment Residuals
Sum of Squares   33.42953  65.49762
Deg. of Freedom        40       110

Residual standard error: 0.771643 
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  40 33.430 0.83574  1.4036 0.08588 .
Residuals 110 65.498 0.59543                  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/1k1tx1322159625.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/wessaorg/rcomp/tmp/2fyjy1322159626.tab") 
> postscript(file="/var/wessaorg/rcomp/tmp/36uis1322159626.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/wessaorg/rcomp/tmp/4i5qy1322159626.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/wessaorg/rcomp/tmp/528pa1322159626.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/wessaorg/rcomp/tmp/6j2rs1322159626.tab") 
+ }
> library(car)
Loading required package: MASS
Loading required package: nnet
Loading required package: survival
Loading required package: splines
> 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/wessaorg/rcomp/tmp/7hcmt1322159626.tab") 
> 
> try(system("convert tmp/36uis1322159626.ps tmp/36uis1322159626.png",intern=TRUE))
character(0)
> try(system("convert tmp/4i5qy1322159626.ps tmp/4i5qy1322159626.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
 12.438   0.157  12.624