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Type 'q()' to quit R. > x <- array(list(NA,3,52,1,38,3,42,3,41,3,24,1,41,2,52,3,45,3,41,2,40,1,34,1,40,3,35,3,46,3,29,1,31,3,46,3,32,3,40,2,38,2,49,1,41,1,NA,3,49,3,65,1,34,1,35,3,42,1,43,2,42,3,59,2,50,2,46,3,37,1,32,3,38,3,30,1,56,2,44,1,58,1,46,2,38,1,58,1,27,3,64,2,36,2,54,1,NA,1,57,1,32,1,30,2,66,3,45,3,35,3,43,3,27,2,49,2,NA,2,39,3,43,3,37,2,33,2,NA,2,49,3,56,2,41,3,40,3,31,2,15,2,38,3,40,3,36,2,31,1,38,2,42,2,56,2,39,2,36,3,44,2,51,3,31,1,55,3,48,3,47,1,43,1,44,2,44,1,37,3,45,1,37,3,31,2,36,3,37,1,30,1,60,2,38,3,71,1,60,3,53,1,40,2,53,2,56,3,57,3,31,1,38,3,49,3,51,3,40,2,73,3,37,3,32,3,49,3,44,1,64,3,34,1,50,3,53,3,53,3,31,2,45,3,31,2,58,3,48,2,56,2,41,2,50,3,37,3,NA,1,70,1,47,3,49,3,47,2,51,1,39,3,43,3,26,3,42,2,45,1,43,3,52,3,45,3,52,2,31,3,42,2,37,3,49,3,43,2,45,3,43,3,47,3,32,3,56,1,47,3,39,2,41,3,38,3,46,1,NA,1,45,3),dim=c(2,160),dimnames=list(c('Var','AgeGroup'),1:160)) > y <- array(NA,dim=c(2,160),dimnames=list(c('Var','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 = 'Variance' > xlab = 'Age Group' > main = 'Mother age at gestation and Childs 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$_version), Office for Research Development and Education, URL http://www.wessa.net/Ian.Holliday/rwasp_STARS_Bullying_Study_alt.wasp/ > #Source of accompanying publication: > #Technical description: > cat1 <- as.numeric(par1) # > cat2<- as.numeric(par2) # > intercept<-as.logical(par3) > x <- t(x) > x1<-as.numeric(x[,cat1]) > f1<-as.character(x[,cat2]) > xdf<-data.frame(x1,f1) > (V1<-dimnames(y)[[1]][cat1]) [1] "Var" > (V2<-dimnames(y)[[1]][cat2]) [1] "AgeGroup" > names(xdf)<-c('Response', 'Treatment') > if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, data = xdf) ) Call: lm(formula = Response ~ Treatment, data = xdf) Coefficients: (Intercept) Treatment2 Treatment3 43.9730 -1.4254 -0.1216 > (aov.xdf<-aov(lmxdf) ) Call: aov(formula = lmxdf) Terms: Treatment Residuals Sum of Squares 55.427 14908.743 Deg. of Freedom 2 150 Residual standard error: 9.969534 Estimated effects may be unbalanced 7 observations deleted due to missingness > (anova.xdf<-anova(lmxdf) ) Analysis of Variance Table Response: Response Df Sum Sq Mean Sq F value Pr(>F) Treatment 2 55.4 27.7 0.2788 0.757 Residuals 150 14908.7 99.4 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'ANOVA Model', length(lmxdf$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$coefficients[i], digits=3),,FALSE) + } > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/1jfx41259935191.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'ANOVA Statistics', 5+1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, ' ',,TRUE) > a<-table.element(a, 'Df',,FALSE) > a<-table.element(a, 'Sum Sq',,FALSE) > a<-table.element(a, 'Mean Sq',,FALSE) > a<-table.element(a, 'F value',,FALSE) > a<-table.element(a, 'Pr(>F)',,FALSE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, V2,,TRUE) > a<-table.element(a, anova.xdf$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/html/rcomp/tmp/2tvlo1259935191.tab") > postscript(file="/var/www/html/rcomp/tmp/3frv31259935191.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/html/rcomp/tmp/4mx781259935191.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/html/rcomp/tmp/5ejsf1259935191.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/html/rcomp/tmp/65t1k1259935191.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/html/rcomp/tmp/7cwcl1259935191.tab") > > system("convert tmp/3frv31259935191.ps tmp/3frv31259935191.png") > system("convert tmp/4mx781259935191.ps tmp/4mx781259935191.png") > > > proc.time() user system elapsed 0.576 0.283 0.668