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Data X:
70.8 66.67 69.6 66.33 69.87 64.33 67.47 64 67.6 63.33 67.13 61.33 66.27 64.67 66.73 63 68.07 60.67 67.8 63.67 64.8 60.67 64.6 61.67 64.2 62.33 64.2 60.33 63.67 59.67 61 60.33 59.67 59.33 59.67 58.67 59.8 58.67 60.73 59.33 59.4 57.33 58.07 59.33 57.47 56 70.73 53.67 72.87 58.67 66 49.33 66.07 71.33 66 70.33 66.27 69 64 66 63.67 66 63.73 63.33 63.33 65.33 63.53 64.33 63.53 64 62.87 61.67 59.53 63.67 62.8 64.67 60.8 61.67 59.8 62 56.67 61.33 57.67 63.67 58.4 61.33 55.47 62.33 56.2 59.67 71.53 59.33 68.67 61.67 65.67 58.67 66.73 58 67.33 56.67 66.73 59.67 66.87 58 65.8 57 64.73 57.67 65.47 58.67 63.6 55.33 64.07 56 64.67 55.67 63.73 53.33 62.53 53.67 61.93 51 62.67 47 62.8 4.33 61.33 70 62.6 68.67 59.13 67.67 61.27 66 59.47 65.67 57.87 65.67 59.73 63.67 61.4 63.67 58.8 64 58.33 62 57.47 62 57.13 61.67 55 61.67 51.53 63.33 72.73 61 73 62.33 70.8 60.33 70.07 60.33 71.67 60.67 71.07 57.67 70.67 58.33 70.73 58 70.73 57.33 68.6 56.67 69.6 58 66.47 55.33 67.07 55.67 68.67 54.67 66.93 56.33 65.93 55 68.87 55 66.53 54.67 65.8 54.33 66.6 49 66 48.33 65 49.67 66.8 43.67 65.6 6.33 66 3 65.67 66.67 64.67 67.33 65.07 65.33 64.67 66 65.07 65.67 65.2 66.67 64.87 65.67 63.47 65 62.6 64.67 64.07 66.67 63.73 63.67 64.67 63.33 61.6 63.67 61.6 63.33 60.47 63.67 61.27 63 63 61.67 61.47 61.33 60.87 60.67 61.67 60 62.87 61.67 62.4 61.33 59.73 58.67 60.13 60.33 58.8 59.67 59.6 59.33 58.93 59.67 60.13 61 58.2 61 58.27 60 58.27 60 55.07 58.67 53.87 58.33 52.33 58 47.2 56.33 37.93 54.67 72.73 55.33 70.07 54 70.67 52.67 72.07 44 68.8 65.67 68.8 65 67.47 66.33 66.73 64 66.53 62.33 66 61.33 67.6 63 66 63.67 66 62 66.53 61.33 65.8 64.67 64.27 62.67 64.67 64 64.6 61 64.13 60.67 65.47 59.67 62.93 60.33 63.53 56.67 62.13 56.67 63.87 54.33 64.67 51 63.33 51 63.13 47 62.8 68 62.4 65 62.4 64 62.6 64 61.47 64 62.2 62 63 61 61.8 60 59.73 60 60.33 62 60.13 60 59.53 59 59 61 55.93 60 41.87 60 36.33 58 71.67 58 71.47 60 70.47 58 69.53 59 70.73 56 69.93 54 68.73 51 67.53 47
Names of X columns:
X1 X2
Response : Variable 1
Factor : Variable 2
Factor : Variable 3
Include Intercept Term ?
TRUE
FALSE
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
cat1 <- as.numeric(par1) # cat2<- as.numeric(par2) # cat3 <- as.numeric(par3) intercept<-as.logical(par4) x <- t(x) x1<-as.numeric(x[,cat1]) f1<-as.character(x[,cat2]) f2 <- as.character(x[,cat3]) xdf<-data.frame(x1,f1, f2) (V1<-dimnames(y)[[1]][cat1]) (V2<-dimnames(y)[[1]][cat2]) (V3 <-dimnames(y)[[1]][cat3]) names(xdf)<-c('Response', 'Treatment_A', 'Treatment_B') if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment_A * Treatment_B- 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment_A * Treatment_B, 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$coefficients)+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, lmxdf$call['formula'],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$coefficients[i], digits=3),,FALSE) } a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'ANOVA Statistics', 5+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, ' ',,TRUE) a<-table.element(a, 'Df',,FALSE) a<-table.element(a, 'Sum Sq',,FALSE) a<-table.element(a, 'Mean Sq',,FALSE) a<-table.element(a, 'F value',,FALSE) a<-table.element(a, 'Pr(>F)',,FALSE) a<-table.row.end(a) for(i in 1 : length(rownames(anova.xdf))-1){ a<-table.row.start(a) a<-table.element(a,rownames(anova.xdf)[i] ,,TRUE) a<-table.element(a, anova.xdf$Df[1],,FALSE) a<-table.element(a, round(anova.xdf$'Sum Sq'[i], digits=3),,FALSE) a<-table.element(a, round(anova.xdf$'Mean Sq'[i], digits=3),,FALSE) a<-table.element(a, round(anova.xdf$'F value'[i], digits=3),,FALSE) a<-table.element(a, round(anova.xdf$'Pr(>F)'[i], 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$'Df'[i+1],,FALSE) a<-table.element(a, round(anova.xdf$'Sum Sq'[i+1], digits=3),,FALSE) a<-table.element(a, round(anova.xdf$'Mean Sq'[i+1], digits=3),,FALSE) a<-table.element(a, ' ',,FALSE) a<-table.element(a, ' ',,FALSE) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') bitmap(file='anovaplot.png') boxplot(Response ~ Treatment_A + Treatment_B, data=xdf, xlab=V2, ylab=V1, main='Boxplots of ANOVA Groups') dev.off() bitmap(file='designplot.png') xdf2 <- xdf # to preserve xdf make copy for function names(xdf2) <- c(V1, V2, V3) plot.design(xdf2, main='Design Plot of Group Means') dev.off() bitmap(file='interactionplot.png') interaction.plot(xdf$Treatment_A, xdf$Treatment_B, xdf$Response, xlab=V2, ylab=V1, trace.label=V3, main='Possible Interactions Between Anova Groups') dev.off() if(intercept==TRUE){ thsd<-TukeyHSD(aov.xdf) names(thsd) <- c(V2, V3, paste(V2, ':', V3, sep='')) bitmap(file='TukeyHSDPlot.png') layout(matrix(c(1,2,3,3), 2,2)) plot(thsd, las=1) dev.off() } if(intercept==TRUE){ ntables<-length(names(thsd)) 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(nt in 1:ntables){ for(i in 1:length(rownames(thsd[[nt]]))){ a<-table.row.start(a) a<-table.element(a,rownames(thsd[[nt]])[i], 1, TRUE) for(j in 1:4){ a<-table.element(a,round(thsd[[nt]][i,j], digits=3), 1, FALSE) } a<-table.row.end(a) } } # end nt a<-table.end(a) table.save(a,file='hsdtable.tab') }#end if hsd tables 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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