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Data X:
21 7.5 26 2.5 22 6.0 22 6.5 18 1.0 23 1.0 12 5.5 20 8.5 22 6.5 21 4.5 19 2.0 22 5.0 15 0.5 20 5.0 19 5.0 18 2.5 15 5.0 20 5.5 21 3.5 21 3.0 15 4.0 16 0.5 23 6.5 21 4.5 18 7.5 25 5.5 9 4.0 30 7.5 20 7.0 23 4.0 16 5.5 16 2.5 19 5.5 25 0.5 25 3.5 18 2.5 23 4.5 21 4.5 10 4.5 14 6.0 22 2.5 26 5.0 23 0.0 23 5.0 24 6.5 24 5.0 18 6.0 23 4.5 15 5.5 19 1.0 16 7.5 25 6.0 23 5.0 17 1.0 19 5.0 21 6.5 18 7.0 27 4.5 21 0.0 13 8.5 8 3.5 29 7.5 28 3.5 23 6.0 21 1.5 19 9.0 19 3.5 20 3.5 18 4.0 19 6.5 17 7.5 19 6.0 25 5.0 19 5.5 22 3.5 23 7.5 26 1.0 14 6.5 28 NA 16 6.5 24 6.5 20 7.0 12 3.5 24 1.5 22 4.0 12 7.5 22 4.5 20 0.0 10 3.5 23 5.5 17 5.0 22 4.5 24 2.5 18 7.5 21 7.0 20 0.0 20 4.5 22 3.0 19 1.5 20 3.5 26 2.5 23 5.5 24 8.0 21 1.0 21 5.0 19 4.5 8 3.0 17 3.0 20 8.0 11 2.5 8 7.0 15 0.0 18 1.0 18 3.5 19 5.5 19 5.5 23 0.5 22 7.5 21 9 25 9.5 30 8.5 17 7 27 8 23 10 23 7 18 8.5 18 9 23 9.5 19 4 15 6 20 8 16 5.5 24 9.5 25 7.5 25 7 19 7.5 19 8 16 7 19 7 19 6 23 10 21 2.5 22 9 19 8 20 6 20 8.5 3 6 23 9 14 8 23 8 20 9 15 5.5 13 5 16 7 7 5.5 24 9 17 2 24 8.5 24 9 19 8.5 25 9 20 7.5 28 10 23 9 27 7.5 18 6 28 10.5 21 8.5 19 8 23 10 27 10.5 22 6.5 28 9.5 25 8.5 21 7.5 22 5 28 8 20 10 29 7 25 7.5 25 7.5 20 9.5 20 6 16 10 20 7 20 3 23 6 18 7 25 10 18 7 19 3.5 25 8 25 10 25 5.5 24 6 19 6.5 26 6.5 10 8.5 17 4 13 9.5 17 8 30 8.5 25 5.5 4 7 16 9 21 8 23 10 22 8 17 6 20 8 20 5 22 9 16 4.5 23 8.5 16 7 0 9.5 18 8.5 25 7.5 23 7.5 12 5 18 7 24 8 11 5.5 18 8.5 14 7.5 23 9.5 24 7 29 8 18 8.5 15 3.5 29 6.5 16 6.5 19 10.5 22 8.5 16 8 23 10 23 10 19 9.5 4 9 20 10 24 7.5 20 4.5 4 4.5 24 0.5 22 6.5 16 4.5 3 5.5 15 5 24 6 17 4 20 8 27 10.5 23 8.5 26 6.5 23 8 17 8.5 20 5.5 22 7 19 5 24 3.5 19 5 23 9 15 8.5 27 5 26 9.5 22 3 22 1.5 18 6 15 0.5 22 6.5 27 7.5 10 4.5 20 8 17 9 23 7.5 19 8.5 13 7 27 9.5 23 6.5 16 9.5 25 6 2 8 26 9.5 20 8 23 8 22 9 24 5
Names of X columns:
NUMERACYTOT Ex
Response Variable (column number)
Factor Variable (column number)
Include Intercept Term ?
FALSE
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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