R version 3.1.0 (2014-04-10) -- "Spring Dance"
Copyright (C) 2014 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- array(list(1
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+ ,dim=c(3
+ ,150)
+ ,dimnames=list(c('Vetesort'
+ ,'Godning'
+ ,'Utbyte')
+ ,1:150))
>  y <- array(NA,dim=c(3,150),dimnames=list(c('Vetesort','Godning','Utbyte'),1:150))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par4 = 'TRUE'
> par3 = '1'
> par2 = '2'
> par1 = '3'
> ylab = 'Y Variable Name'
> xlab = 'X Variable Name'
> main = 'Title Goes Here'
> par4 <- 'TRUE'
> par3 <- '1'
> par2 <- '2'
> par1 <- '3'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: aston2
> #To cite this work: Ian E. Holliday, 2012, Two-Way ANOVA (v1.0.3) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/Ian.Holliday/rwasp_Two%20Factor%20ANOVA.wasp/
> #Source of accompanying publication: 
> #
> cat1 <- as.numeric(par1) #
> cat2<- as.numeric(par2) #
> cat3 <- as.numeric(par3)
> intercept<-as.logical(par4)
> x <- t(x)
> x1<-as.numeric(x[,cat1])
> f1<-as.character(x[,cat2])
> f2 <- as.character(x[,cat3])
> xdf<-data.frame(x1,f1, f2)
> (V1<-dimnames(y)[[1]][cat1])
[1] "Utbyte"
> (V2<-dimnames(y)[[1]][cat2])
[1] "Godning"
> (V3 <-dimnames(y)[[1]][cat3])
[1] "Vetesort"
> names(xdf)<-c('Response', 'Treatment_A', 'Treatment_B')
> if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment_A * Treatment_B- 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment_A * Treatment_B, data = xdf) )

Call:
lm(formula = Response ~ Treatment_A * Treatment_B, data = xdf)

Coefficients:
              (Intercept)               Treatment_A2  
                7.950e+01                 -5.333e+00  
             Treatment_A3               Treatment_A4  
                3.500e+00                  1.000e+00  
             Treatment_A5               Treatment_B2  
                1.167e+00                 -6.500e+00  
             Treatment_B3               Treatment_B4  
                8.167e+00                  6.000e+00  
             Treatment_B5  Treatment_A2:Treatment_B2  
               -3.333e-01                  1.833e+00  
Treatment_A3:Treatment_B2  Treatment_A4:Treatment_B2  
                1.710e-14                  6.667e-01  
Treatment_A5:Treatment_B2  Treatment_A2:Treatment_B3  
                3.833e+00                  1.667e+00  
Treatment_A3:Treatment_B3  Treatment_A4:Treatment_B3  
               -1.333e+00                 -2.167e+00  
Treatment_A5:Treatment_B3  Treatment_A2:Treatment_B4  
                1.000e+00                  2.333e+00  
Treatment_A3:Treatment_B4  Treatment_A4:Treatment_B4  
               -2.000e+00                 -3.333e+00  
Treatment_A5:Treatment_B4  Treatment_A2:Treatment_B5  
               -3.333e+00                  2.833e+00  
Treatment_A3:Treatment_B5  Treatment_A4:Treatment_B5  
                6.667e-01                  3.333e+00  
Treatment_A5:Treatment_B5  
                4.500e+00  

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

Terms:
                Treatment_A Treatment_B Treatment_A:Treatment_B Residuals
Sum of Squares      800.040    2991.973                 232.160  2065.000
Deg. of Freedom           4           4                      16       125

Residual standard error: 4.06448
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_A               4  800.04  200.01 12.1071 2.387e-08 ***
Treatment_B               4 2991.97  747.99 45.2780 < 2.2e-16 ***
Treatment_A:Treatment_B  16  232.16   14.51  0.8783    0.5951    
Residuals               125 2065.00   16.52                      
---
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$coefficients)+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, lmxdf$call['formula'],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$coefficients[i], digits=3),,FALSE)
+ }
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/1r9ca1400172444.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, ' ',,TRUE)
> a<-table.element(a, 'Df',,FALSE)
> a<-table.element(a, 'Sum Sq',,FALSE)
> a<-table.element(a, 'Mean Sq',,FALSE)
> a<-table.element(a, 'F value',,FALSE)
> a<-table.element(a, 'Pr(>F)',,FALSE)
> a<-table.row.end(a)
> for(i in 1 : length(rownames(anova.xdf))-1){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(anova.xdf)[i] ,,TRUE)
+ a<-table.element(a, anova.xdf$Df[1],,FALSE)
+ a<-table.element(a, round(anova.xdf$'Sum Sq'[i], digits=3),,FALSE)
+ a<-table.element(a, round(anova.xdf$'Mean Sq'[i], digits=3),,FALSE)
+ a<-table.element(a, round(anova.xdf$'F value'[i], digits=3),,FALSE)
+ a<-table.element(a, round(anova.xdf$'Pr(>F)'[i], 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$'Df'[i+1],,FALSE)
> a<-table.element(a, round(anova.xdf$'Sum Sq'[i+1], digits=3),,FALSE)
> a<-table.element(a, round(anova.xdf$'Mean Sq'[i+1], digits=3),,FALSE)
> a<-table.element(a, ' ',,FALSE)
> a<-table.element(a, ' ',,FALSE)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/2fb2w1400172444.tab") 
> postscript(file="/var/wessaorg/rcomp/tmp/3hgjb1400172444.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> boxplot(Response ~ Treatment_A + Treatment_B, data=xdf, xlab=V2, ylab=V1, main='Boxplots of ANOVA Groups')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4n5a21400172444.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> xdf2 <- xdf # to preserve xdf make copy for function
> names(xdf2) <- c(V1, V2, V3)
> plot.design(xdf2, main='Design Plot of Group Means')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/5txmo1400172444.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> interaction.plot(xdf$Treatment_A, xdf$Treatment_B, xdf$Response, xlab=V2, ylab=V1, trace.label=V3, main='Possible Interactions Between Anova Groups')
> dev.off()
null device 
          1 
> if(intercept==TRUE){
+ thsd<-TukeyHSD(aov.xdf)
+ names(thsd) <- c(V2, V3, paste(V2, ':', V3, sep=''))
+ postscript(file="/var/wessaorg/rcomp/tmp/6tqoo1400172444.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
+ layout(matrix(c(1,2,3,3), 2,2))
+ plot(thsd, las=1)
+ dev.off()
+ }
null device 
          1 
> if(intercept==TRUE){
+ ntables<-length(names(thsd))
+ 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(nt in 1:ntables){
+ for(i in 1:length(rownames(thsd[[nt]]))){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(thsd[[nt]])[i], 1, TRUE)
+ for(j in 1:4){
+ a<-table.element(a,round(thsd[[nt]][i,j], digits=3), 1, FALSE)
+ }
+ a<-table.row.end(a)
+ }
+ } # end nt
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/7jcoy1400172444.tab") 
+ }#end if hsd tables
> 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/89wi51400172444.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/wessaorg/rcomp/tmp/93brt1400172444.tab") 
> 
> try(system("convert tmp/3hgjb1400172444.ps tmp/3hgjb1400172444.png",intern=TRUE))
character(0)
> try(system("convert tmp/4n5a21400172444.ps tmp/4n5a21400172444.png",intern=TRUE))
character(0)
> try(system("convert tmp/5txmo1400172444.ps tmp/5txmo1400172444.png",intern=TRUE))
character(0)
> try(system("convert tmp/6tqoo1400172444.ps tmp/6tqoo1400172444.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  5.069   0.412   5.496