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Data X:
4.35 1 12.7 1 18.1 1 17.85 1 16.6 0 12.6 1 17.1 1 19.1 0 16.1 1 13.35 0 18.4 0 14.7 1 10.6 1 12.6 1 16.2 1 13.6 1 18.9 1 14.1 1 14.5 1 16.15 0 14.75 1 14.8 1 12.45 1 12.65 1 17.35 1 8.6 1 18.4 0 16.1 1 11.6 1 17.75 1 15.25 1 17.65 1 16.35 0 17.65 0 13.6 1 14.35 0 14.75 0 18.25 1 9.9 0 16 1 18.25 1 16.85 0 14.6 1 13.85 1 18.95 1 15.6 0 14.85 0 11.75 0 18.45 0 15.9 1 17.1 0 16.1 1 19.9 0 10.95 1 18.45 0 15.1 1 15 0 11.35 0 15.95 1 18.1 0 14.6 1 15.4 1 15.4 1 17.6 1 13.35 1 19.1 0 15.35 1 7.6 0 13.4 0 13.9 0 19.1 1 15.25 0 12.9 1 16.1 0 17.35 0 13.15 0 12.15 0 12.6 1 10.35 1 15.4 1 9.6 1 18.2 0 13.6 0 14.85 1 14.75 0 14.1 0 14.9 0 16.25 0 19.25 1 13.6 1 13.6 0 15.65 0 12.75 1 14.6 0 9.85 1 12.65 1 19.2 0 16.6 1 11.2 1 15.25 1 11.9 0 13.2 0 16.35 0 12.4 1 15.85 1 18.15 1 11.15 1 15.65 0 17.75 0 7.65 0 12.35 1 15.6 1 19.3 0 15.2 0 17.1 0 15.6 1 18.4 1 19.05 0 18.55 0 19.1 0 13.1 1 12.85 1 9.5 1 4.5 1 11.85 0 13.6 1 11.7 1 12.4 1 13.35 0 11.4 0 14.9 1 19.9 0 11.2 1 14.6 1 17.6 0 14.05 1 16.1 0 13.35 1 11.85 1 11.95 0 14.75 1 15.15 0 13.2 1 16.85 0 7.85 1 7.7 0 12.6 0 7.85 1 10.95 1 12.35 0 9.95 1 14.9 1 16.65 0 13.4 1 13.95 0 15.7 0 16.85 1 10.95 1 15.35 0 12.2 1 15.1 0 17.75 0 15.2 1 14.6 0 16.65 0 8.1 1
Names of X columns:
TOT gender
Response Variable (column number)
Factor Variable (column number)
Include Intercept Term ?
TRUE
TRUE
FALSE
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
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) ) load(file='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='mytable.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='mytable1.tab') bitmap(file='anovaplot.png') boxplot(Response ~ Treatment, data=xdf, xlab=V2, ylab=V1) dev.off() if(intercept==TRUE){ 'Tukey Plot' thsd<-TukeyHSD(aov.xdf) bitmap(file='TukeyHSDPlot.png') 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='mytable2.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='mytable2.tab') } library(car) 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='mytable3.tab')
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