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(77
+ ,77
+ ,58
+ ,51
+ ,53
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+ ,NA
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+ ,79
+ ,81)
+ ,dim=c(2
+ ,200)
+ ,dimnames=list(c('weightloss'
+ ,'rptwloss')
+ ,1:200))
>  y <- array(NA,dim=c(2,200),dimnames=list(c('weightloss','rptwloss'),1:200))
>  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 = '2'
> par1 = '1'
> ylab = 'Y Variable Name'
> xlab = 'X Variable Name'
> main = 'Title Goes Here'
> par3 <- 'FALSE'
> par2 <- '2'
> 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] "weightloss"
> (V2<-dimnames(y)[[1]][cat2])
[1] "rptwloss"
> 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  Treatment107  Treatment124   Treatment41  
      101.00         97.50        102.00        119.00         39.00  
 Treatment44   Treatment45   Treatment47   Treatment49   Treatment50  
       46.00         45.67         48.00         50.00         50.80  
 Treatment51   Treatment52   Treatment53   Treatment54   Treatment55  
       53.20         52.20         53.60         55.20         55.85  
 Treatment56   Treatment57   Treatment58   Treatment59   Treatment60  
       67.67         55.00         56.60         59.25         59.50  
 Treatment61   Treatment62   Treatment63   Treatment64   Treatment65  
       61.38         63.00         64.25         63.83         65.00  
 Treatment66   Treatment67   Treatment68   Treatment69   Treatment70  
       64.71         67.00         68.57         68.50         69.50  
 Treatment71   Treatment73   Treatment74   Treatment75   Treatment76  
       71.20         71.75         73.00         75.17         76.20  
 Treatment77   Treatment78   Treatment79   Treatment80   Treatment81  
       76.75         80.00         79.00         80.33         79.00  
 Treatment82   Treatment83   Treatment84   Treatment85   Treatment86  
       83.00         84.00         83.00         82.00         87.25  
 Treatment87   Treatment89   Treatment90   Treatment91   Treatment93  
       88.00         87.00         84.00         90.00         88.00  
 Treatment94   Treatment95   Treatment98   TreatmentNA  
       96.00         96.00         97.00         61.24  

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

Terms:
                Treatment Residuals
Sum of Squares   897340.5   13931.5
Deg. of Freedom        54       146

Residual standard error: 9.768368 
Estimated effects are balanced
> (anova.xdf<-anova(lmxdf) )
Analysis of Variance Table

Response: Response
           Df Sum Sq Mean Sq F value    Pr(>F)    
Treatment  54 897341 16617.4  174.15 < 2.2e-16 ***
Residuals 146  13931    95.4                      
---
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/1cifa1338546488.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/2h7yf1338546488.tab") 
> postscript(file="/var/wessaorg/rcomp/tmp/3erjw1338546488.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/4hjn41338546488.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/5ni3t1338546488.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/6oe2s1338546488.tab") 
+ }
> library(car)
Loading required package: MASS
Loading required package: nnet
Loading required package: survival
Loading required package: splines
> 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/7luws1338546488.tab") 
> 
> try(system("convert tmp/3erjw1338546488.ps tmp/3erjw1338546488.png",intern=TRUE))
character(0)
> try(system("convert tmp/4hjn41338546488.ps tmp/4hjn41338546488.png",intern=TRUE))
convert: unable to open image `tmp/4hjn41338546488.ps': No such file or directory @ blob.c/OpenBlob/2480.
convert: missing an image filename `tmp/4hjn41338546488.png' @ convert.c/ConvertImageCommand/2838.
character(0)
Warning message:
running command 'convert tmp/4hjn41338546488.ps tmp/4hjn41338546488.png' had status 1 
> 
> 
> proc.time()
   user  system elapsed 
  0.839   0.161   0.992