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(0.18,'Control','Male',-0.45,'Control','Male',1.19,'Control','Male',0.63,'Control','Female',0.80,'Control','Female',-1.09,'Control','Female',-1.24,'Control','Female',1.17,'Control','Female',-0.11,'TreatA','Male',1.68,'TreatA','Male',2.44,'TreatA','Male',0.30,'TreatA','Male',2.59,'TreatA','Female',2.01,'TreatA','Female',1.01,'TreatA','Female',1.95,'TreatA','Female',-0.23,'TreatB','Male',1.87,'TreatB','Male',-0.23,'TreatB','Male',-0.42,'TreatB','Male',3.09,'TreatB','Female',0.79,'TreatB','Female',-0.82,'TreatB','Female',3.23,'TreatB','Female'),dim=c(3,24),dimnames=list(c('Response','Treatment_A','Treatment_B'),1:24))
>  y <- array(NA,dim=c(3,24),dimnames=list(c('Response','Treatment_A','Treatment_B'),1:24))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
There were 48 warnings (use warnings() to see them)
> par4 = 'TRUE'
> par3 = '3'
> par2 = '2'
> par1 = '1'
> ylab = 'Y Variable Name'
> xlab = 'X Variable Name'
> main = 'Title Goes Here'
> 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] "Response"
> (V2<-dimnames(y)[[1]][cat2])
[1] "Treatment_A"
> (V3 <-dimnames(y)[[1]][cat3])
[1] "Treatment_B"
> 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_ATreatA  
                           0.0540                             1.8360  
                Treatment_ATreatB                    Treatment_BMale  
                           1.5185                             0.2527  
Treatment_ATreatA:Treatment_BMale  Treatment_ATreatB:Treatment_BMale  
                          -1.0652                            -1.5777  

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

Terms:
                Treatment_A Treatment_B Treatment_A:Treatment_B Residuals
Sum of Squares     7.175775    2.459490                2.491774 26.922812
Deg. of Freedom           2           1                       2        18

Residual standard error: 1.222993 
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              2  7.1758  3.5879  2.3988 0.1192
Treatment_B              1  2.4595  2.4595  1.6444 0.2160
Treatment_A:Treatment_B  2  2.4918  1.2459  0.8330 0.4508
Residuals               18 26.9228  1.4957               
> 
> #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$coefficients)+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, lmxdf$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$coefficients[i], digits=3),,FALSE)
+ }
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/1jffs1260631949.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, ' ',,TRUE)
> a<-table.element(a, 'Df',,FALSE)
> a<-table.element(a, 'Sum Sq',,FALSE)
> a<-table.element(a, 'Mean Sq',,FALSE)
> a<-table.element(a, 'F value',,FALSE)
> a<-table.element(a, 'Pr(>F)',,FALSE)
> a<-table.row.end(a)
> for(i in 1 : length(rownames(anova.xdf))-1){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(anova.xdf)[i] ,,TRUE)
+ a<-table.element(a, anova.xdf$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$Df[i],,FALSE)
> a<-table.element(a, round(anova.xdf$'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/www/rcomp/tmp/24whl1260631949.tab") 
> postscript(file="/var/www/rcomp/tmp/3idqx1260631949.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> boxplot(Response ~ Treatment_A + Treatment_B, data=xdf, xlab=V2, ylab=V1)
> dev.off()
null device 
          1 
> if(intercept==TRUE){
+ postscript(file="/var/www/rcomp/tmp/4rjqo1260631949.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
+ thsd<-TukeyHSD(aov.xdf)
+ 
+ #plot(thsd, las=1)
+ 
+ op <- par(mfrow=c(3,1))
+ plot(thsd, las=1)
+ par(op)
+ 
+ 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/www/rcomp/tmp/5lb441260631949.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/67s6k1260631950.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/773141260631950.tab") 
> 
> try(system("convert tmp/3idqx1260631949.ps tmp/3idqx1260631949.png",intern=TRUE))
character(0)
> try(system("convert tmp/4rjqo1260631949.ps tmp/4rjqo1260631949.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.860   0.560   1.361