R version 2.15.1 (2012-06-22) -- "Roasted Marshmallows"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- array(list(1
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+ ,dim=c(3
+ ,151)
+ ,dimnames=list(c('MOMAGE'
+ ,'MC30VRB'
+ ,'WISCRY7V')
+ ,1:151))
>  y <- array(NA,dim=c(3,151),dimnames=list(c('MOMAGE','MC30VRB','WISCRY7V'),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 = 'FALSE'
> par2 = '3'
> par1 = '1'
> ylab = 'Y Variable Name'
> xlab = 'X Variable Name'
> main = 'Title Goes Here'
> par3 <- 'FALSE'
> par2 <- '3'
> par1 <- '1'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: aston2
> #To cite this work: Ian E. Holliday, 2012, One-Way-Between-Groups ANOVA (v1.0.4) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/Ian.Holliday/rwasp_One%20Factor%20ANOVA.wasp/
> #Source of accompanying publication: 
> #
> 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] "WISCRY7V"
> 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 - 1, data = xdf)

Coefficients:
Treatment100  Treatment101  Treatment102  Treatment103  Treatment106  
       2.333         2.143         2.000         2.000         2.500  
Treatment107  Treatment108  Treatment109  Treatment111  Treatment112  
       2.000         2.000         2.000         2.333         3.000  
Treatment115   Treatment68   Treatment70   Treatment72   Treatment73  
       2.000         2.500         2.000         3.000         3.000  
 Treatment75   Treatment77   Treatment78   Treatment79   Treatment80  
       1.600         2.250         1.667         2.000         1.667  
 Treatment81   Treatment82   Treatment84   Treatment85   Treatment86  
       3.000         1.000         1.000         2.000         2.889  
 Treatment87   Treatment88   Treatment90   Treatment91   Treatment92  
       1.857         2.429         2.400         2.200         2.833  
 Treatment94   Treatment95   Treatment96   Treatment97   Treatment98  
       2.125         2.273         2.600         2.500         2.400  

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

Terms:
                Treatment Residuals
Sum of Squares   792.0757   76.9243
Deg. of Freedom        35       116

Residual standard error: 0.8143343 
Estimated effects are balanced
> (anova.xdf<-anova(lmxdf) )
Analysis of Variance Table

Response: Response
           Df Sum Sq Mean Sq F value    Pr(>F)    
Treatment  35 792.08 22.6307  34.127 < 2.2e-16 ***
Residuals 116  76.92  0.6631                      
---
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/1to8v1351876917.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/2r8hg1351876917.tab") 
> postscript(file="/var/wessaorg/rcomp/tmp/353oq1351876917.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){
+ 'Tukey Plot'
+ thsd<-TukeyHSD(aov.xdf)
+ postscript(file="/var/wessaorg/rcomp/tmp/461l01351876917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
+ plot(thsd)
+ dev.off()
+ }
> 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/51g9l1351876917.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/6b6ha1351876917.tab") 
+ }
> library(car)
Loading required package: MASS
Loading required package: nnet
> lt.lmxdf<-leveneTest(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/wessaorg/rcomp/tmp/7x7dl1351876917.tab") 
> 
> try(system("convert tmp/353oq1351876917.ps tmp/353oq1351876917.png",intern=TRUE))
character(0)
> try(system("convert tmp/461l01351876917.ps tmp/461l01351876917.png",intern=TRUE))
convert: unable to open image `tmp/461l01351876917.ps':  @ error/blob.c/OpenBlob/2587.
convert: missing an image filename `tmp/461l01351876917.png' @ error/convert.c/ConvertImageCommand/3011.
character(0)
attr(,"status")
[1] 1
Warning message:
running command 'convert tmp/461l01351876917.ps tmp/461l01351876917.png' had status 1 
> 
> 
> proc.time()
   user  system elapsed 
  1.123   0.186   1.287