x <- array(list(36,3,36,1,56,3,48,3,32,3,44,1,39,2,34,3,41,3,50,2,39,1,62,1,52,3,37,3,50,3,41,1,55,3,41,3,56,3,39,2,52,2,46,1,44,1,48,3,41,3,50,1,50,1,44,3,52,1,54,2,44,3,52,2,37,2,52,3,50,1,36,3,50,3,52,1,55,2,31,1,36,1,49,2,42,1,37,1,41,3,30,2,52,2,30,1,41,1,44,1,66,1,48,2,43,3,57,3,46,3,54,3,48,2,48,2,52,2,62,3,58,3,58,2,62,2,48,2,46,3,34,2,66,3,52,3,55,2,55,2,57,3,56,3,55,2,56,1,54,2,55,2,46,2,52,2,32,3,44,2,46,3,59,1,46,3,46,3,54,1,66,1,56,2,59,1,57,3,52,1,48,3,44,2,41,3,50,1,48,1,48,2,59,3,34,1,46,3,54,1,55,2,54,2,59,3,44,3,54,1,52,3,66,3,44,3,57,2,39,3,60,3,45,3,41,3,50,1,39,3,43,1,48,3,37,3,58,3,46,2,43,3,44,2,34,3,30,2,50,2,39,2,37,3,55,3,48,1,41,1,39,3,36,3,43,2,50,1,55,3,43,3,60,3,48,2,30,1,43,3,39,3,52,3,39,2,39,3,56,2,59,3,46,3,57,2,50,3,54,3,50,3,60,3,59,1,41,3,48,2,59,3,60,3,56,1,56,1,51,3),dim=c(2,160),dimnames=list(c('RespVar','AgeGroup'),1:160)) y <- array(NA,dim=c(2,160),dimnames=list(c('RespVar','AgeGroup'),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 = 'Y Variable Name' xlab = 'X Variable Name' main = 'Title Goes Here' #'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$_version), Office for Research Development and Education, URL http://www.wessa.net/Ian.Holliday/rwasp_STARS_Bullying_Study_alt.wasp/ #Source of accompanying publication: #Technical description: cat1 <- as.numeric(par1) # cat2<- as.numeric(par2) # intercept<-as.logical(par3) x <- t(x) x1<-as.numeric(x[,cat1]) f1<-as.character(x[,cat2]) xdf<-data.frame(x1,f1) (V1<-dimnames(y)[[1]][cat1]) (V2<-dimnames(y)[[1]][cat2]) names(xdf)<-c('Response', 'Treatment') if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, data = xdf) ) (aov.xdf<-aov(lmxdf) ) (anova.xdf<-anova(lmxdf) ) #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab load(file="/var/www/rcomp/createtable") a<-table.start() a<-table.row.start(a) a<-table.element(a,'ANOVA Model', length(lmxdf$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$coefficients[i], digits=3),,FALSE) } a<-table.row.end(a) a<-table.end(a) table.save(a,file="/var/www/rcomp/tmp/1cwxe1259844430.tab") a<-table.start() a<-table.row.start(a) a<-table.element(a,'ANOVA Statistics', 5+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, ' ',,TRUE) a<-table.element(a, 'Df',,FALSE) a<-table.element(a, 'Sum Sq',,FALSE) a<-table.element(a, 'Mean Sq',,FALSE) a<-table.element(a, 'F value',,FALSE) a<-table.element(a, 'Pr(>F)',,FALSE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, V2,,TRUE) a<-table.element(a, anova.xdf$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/2m21z1259844430.tab") postscript(file="/var/www/rcomp/tmp/38r3z1259844430.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) boxplot(Response ~ Treatment, data=xdf, xlab=V2, ylab=V1) dev.off() if(intercept==TRUE){ thsd<-TukeyHSD(aov.xdf) postscript(file="/var/www/rcomp/tmp/4kale1259844430.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/56gmk1259844430.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/6jq471259844430.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/7fpdv1259844430.tab") system("convert tmp/38r3z1259844430.ps tmp/38r3z1259844430.png") system("convert tmp/4kale1259844430.ps tmp/4kale1259844430.png")