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(36
+ ,36
+ ,36
+ ,36
+ ,56
+ ,56
+ ,48
+ ,48
+ ,32
+ ,32
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+ ,55
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+ ,37
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+ ,48
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+ ,37
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+ ,46
+ ,43
+ ,43
+ ,44
+ ,44
+ ,34
+ ,34
+ ,30
+ ,30
+ ,50
+ ,50
+ ,39
+ ,39
+ ,37
+ ,37
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+ ,55
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+ ,48
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+ ,41
+ ,39
+ ,39
+ ,36
+ ,36
+ ,43
+ ,43
+ ,50
+ ,50
+ ,55
+ ,55
+ ,43
+ ,43
+ ,60
+ ,60
+ ,48
+ ,48
+ ,30
+ ,30
+ ,43
+ ,43
+ ,39
+ ,39
+ ,52
+ ,52
+ ,39
+ ,39
+ ,39
+ ,39
+ ,56
+ ,56
+ ,59
+ ,59
+ ,46
+ ,46
+ ,57
+ ,57
+ ,50
+ ,50
+ ,54
+ ,54
+ ,50
+ ,50
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+ ,60
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+ ,48
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+ ,59
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+ ,60
+ ,60
+ ,56
+ ,56
+ ,56
+ ,56
+ ,51
+ ,51)
+ ,dim=c(2
+ ,160)
+ ,dimnames=list(c('30monthIQ'
+ ,'MUMIQ')
+ ,1:160))
>  y <- array(NA,dim=c(2,160),dimnames=list(c('30monthIQ','MUMIQ'),1:160))
>  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 = 'child 30 month IQ'
> xlab = 'Mum verbal IQ'
> main = 'mothers verbal iq and 30 month IQ'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Dr. Ian E. Holliday
> #To cite this work: Ian E. Holliday, 2009, STARS Bullying Study (v1.0.1) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/Ian.Holliday/rwasp_STARS_Bullying_Study_alt.wasp/
> #Source of accompanying publication: 
> #Technical description: 
> 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] "30monthIQ"
> (V2<-dimnames(y)[[1]][cat2])
[1] "MUMIQ"
> 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)  Treatment31  Treatment32  Treatment34  Treatment36  Treatment37  
         30            1            2            4            6            7  
Treatment39  Treatment41  Treatment42  Treatment43  Treatment44  Treatment45  
          9           11           12           13           14           15  
Treatment46  Treatment48  Treatment49  Treatment50  Treatment51  Treatment52  
         16           18           19           20           21           22  
Treatment54  Treatment55  Treatment56  Treatment57  Treatment58  Treatment59  
         24           25           26           27           28           29  
Treatment60  Treatment62  Treatment66  
         30           32           36  

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

Terms:
                Treatment Residuals
Sum of Squares   11417.98      0.00
Deg. of Freedom        26       133

Residual standard error: 4.168612e-15 
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  26  11418  439.15 2.5272e+31 < 2.2e-16 ***
Residuals 133      0    0.00                         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
Warning message:
In anova.lm(lmxdf) :
  ANOVA F-tests on an essentially perfect fit are unreliable
> 
> #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$coefficients)+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, paste(V1, ' ~ ', V2), length(lmxdf$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/www/rcomp/tmp/1e8w01259848176.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/www/rcomp/tmp/2xu8b1259848176.tab") 
> postscript(file="/var/www/rcomp/tmp/38knh1259848176.ps",horizontal=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/www/rcomp/tmp/4h7e81259848176.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
+ plot(thsd)
+ dev.off()
+ 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/54n8m1259848176.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/6ns5f1259848176.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/7bxe81259848176.tab") 
> 
> system("convert tmp/38knh1259848176.ps tmp/38knh1259848176.png")
> system("convert tmp/4h7e81259848176.ps tmp/4h7e81259848176.png")
> 
> 
> proc.time()
   user  system elapsed 
  2.790   0.810   3.403