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Data X:
0 26 1 57 0 37 1 67 1 43 1 52 0 52 1 43 1 84 1 67 1 49 1 70 1 52 0 58 0 68 0 62 1 43 0 56 1 56 0 74 1 65 1 63 0 58 1 57 1 63 1 53 1 57 0 51 1 64 0 53 0 29 0 54 1 58 1 43 1 51 1 53 0 54 1 56 1 61 0 47 1 39 1 48 1 50 1 35 1 30 0 68 1 49 1 61 0 67 1 47 1 56 1 50 1 43 1 67 1 62 1 57 0 41 1 54 0 45 1 48 1 61 0 56 0 41 1 43 0 53 1 44 0 66 1 58 1 46 0 37 0 51 0 51 0 56 1 66 0 37 1 59 0 42 1 38 0 66 0 34 1 53 0 49 0 55 0 49 1 59 0 40 1 58 1 60 0 63 0 56 0 54 1 52 1 34 1 69 0 32 1 48 0 67 1 58 1 57 1 42 1 64 1 58 0 66 1 26 1 61 1 52 0 51 0 55 0 50 0 60 0 56 0 63 1 61 1 52 1 16 1 46 1 56 0 52 1 55 1 50 0 59 1 60 0 52 0 44 1 67 1 52 1 55 1 37 1 54 1 72 1 51 1 48 0 60 1 50 1 63 1 33 1 67 1 46 1 54 0 59 1 61 1 33 1 47 1 69 1 52 0 55 0 41 1 73 0 52 0 50 1 51 0 60 1 56 1 56 0 29 1 66 1 66 1 73 0 55 0 64 0 40 0 46 1 58 0 43 1 61 0 51 1 50 0 52 1 54 0 66 0 61 1 80 0 51 1 56 1 56 1 56 1 53 1 47 0 25 1 47 0 46 0 50 0 39 1 51 0 58 1 35 0 58 0 60 0 62 0 63 1 53 1 46 1 67 1 59 0 64 0 38 1 50 0 48 0 48 0 47 0 66 1 47 1 63 0 58 0 44 1 51 0 43 1 55 1 38 0 45 1 50 1 54 1 57 0 60 0 55 0 56 1 49 1 37 1 59 1 46 0 51 0 58 0 64 1 53 1 48 0 51 0 47 0 59 1 62 1 62 0 51 0 64 0 52 1 67 1 50 1 54 1 58 0 56 1 63 1 31 1 65 0 71 0 50 1 57 0 47 1 47 1 57 0 43 1 41 0 63 1 63 1 56 0 51 1 50 0 22 1 41 0 59 1 56 0 66 0 53 1 42 1 52 0 54 1 44 1 62 0 53 1 50 0 36 0 76 1 66 1 62 0 59 1 47 0 55 0 58 1 60 0 44 0 57 1 45
Names of X columns:
X1 X2
Response Variable (column number)
Factor Variable (column number)
Include Intercept Term ?
0.95
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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