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Data X:
7.5 149 2.5 152 6 139 6.5 148 1 158 1 128 5.5 224 8.5 159 6.5 105 4.5 159 2 167 5 165 0.5 159 5 119 5 176 2.5 54 5 91 5.5 163 3.5 124 3 137 4 121 0.5 153 6.5 148 4.5 221 7.5 188 5.5 149 4 244 7.5 148 7 92 4 150 5.5 153 2.5 94 5.5 156 0.5 146 3.5 132 2.5 161 4.5 105 4.5 97 4.5 151 6 131 2.5 166 5 157 0 111 5 145 6.5 162 5 163 6 59 4.5 187 5.5 109 1 90 7.5 105 6 83 5 116 1 42 5 148 6.5 155 7 125 4.5 116 0 128 8.5 138 3.5 49 7.5 96 3.5 164 6 162 1.5 99 9 202 3.5 186 3.5 66 4 183 6.5 214 7.5 188 6 104 5 177 5.5 126 3.5 76 7.5 99 1 157 6.5 139 NA 78 6.5 162 6.5 108 7 159 3.5 74 1.5 110 4 96 7.5 116 4.5 87 0 97 3.5 127 5.5 106 5 80 4.5 74 2.5 91 7.5 133 7 74 0 114 4.5 140 3 95 1.5 98 3.5 121 2.5 126 5.5 98 8 95 1 110 5 70 4.5 102 3 86 3 130 8 96 2.5 102 7 100 0 94 1 52 3.5 98 5.5 118 5.5 99 0.5 48 7.5 50 9 150 9.5 154 8.5 109 7 68 8 194 10 158 7 159 8.5 67 9 147 9.5 39 4 100 6 111 8 138 5.5 101 9.5 131 7.5 101 7 114 7.5 165 8 114 7 111 7 75 6 82 10 121 2.5 32 9 150 8 117 6 71 8.5 165 6 154 9 126 8 138 8 149 9 145 5.5 120 5 138 7 109 5.5 132 9 172 2 169 8.5 114 9 156 8.5 172 9 68 7.5 89 10 167 9 113 7.5 115 6 78 10.5 118 8.5 87 8 173 10 2 10.5 162 6.5 49 9.5 122 8.5 96 7.5 100 5 82 8 100 10 115 7 141 7.5 165 7.5 165 9.5 110 6 118 10 158 7 146 3 49 6 90 7 121 10 155 7 104 3.5 147 8 110 10 108 5.5 113 6 115 6.5 61 6.5 60 8.5 109 4 68 9.5 111 8 77 8.5 73 5.5 151 7 89 9 78 8 110 10 220 8 65 6 141 8 117 5 122 9 63 4.5 44 8.5 52 7 62 9.5 131 8.5 101 7.5 42 7.5 152 5 107 7 77 8 154 5.5 103 8.5 96 7.5 154 9.5 175 7 57 8 112 8.5 143 3.5 49 6.5 110 6.5 131 10.5 167 8.5 56 8 137 10 86 10 121 9.5 149 9 168 10 140 7.5 88 4.5 168 4.5 94 0.5 51 6.5 48 4.5 145 5.5 66 5 85 6 109 4 63 8 102 10.5 162 8.5 128 6.5 86 8 114 8.5 164 5.5 119 7 126 5 132 3.5 142 5 83 9 94 8.5 81 5 166 9.5 110 3 64 1.5 93 6 104 0.5 105 6.5 49 7.5 88 4.5 95 8 102 9 99 7.5 63 8.5 76 7 109 9.5 117 6.5 57 9.5 120 6 73 8 91 9.5 108 8 105 8 117 9 119 5 31
Names of X columns:
Ex LFM
Response : Variable 1
Factor : Variable 2
Factor : Variable 3
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) # 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<-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='mytable3.tab')
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