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Data X:
1 3 36 2 1 36 3 3 56 4 3 48 5 3 32 6 1 44 7 2 39 8 3 34 9 3 41 10 2 50 11 1 39 12 1 62 13 3 52 14 3 37 15 3 50 16 1 41 17 3 55 18 3 41 19 3 56 20 2 39 21 2 52 22 1 46 23 1 44 24 3 48 25 3 41 26 1 50 27 1 50 28 3 44 29 1 52 30 2 54 31 3 44 32 2 52 33 2 37 34 3 52 35 1 50 36 3 36 37 3 50 38 1 52 39 2 55 40 1 31 41 1 36 42 2 49 43 1 42 44 1 37 45 3 41 46 2 30 47 2 52 48 1 30 49 1 41 50 1 44 51 1 66 52 2 48 53 3 43 54 3 57 55 3 46 56 3 54 57 2 48 58 2 48 59 2 52 60 3 62 61 3 58 62 2 58 63 2 62 64 2 48 65 3 46 66 2 34 67 3 66 68 3 52 69 2 55 70 2 55 71 3 57 72 3 56 73 2 55 74 1 56 75 2 54 76 2 55 77 2 46 78 2 52 79 3 32 80 2 44 81 3 46 82 1 59 83 3 46 84 3 46 85 1 54 86 1 66 87 2 56 88 1 59 89 3 57 90 1 52 91 3 48 92 2 44 93 3 41 94 1 50 95 1 48 96 2 48 97 3 59 98 1 34 99 3 46 100 1 54 101 2 55 102 2 54 103 3 59 104 3 44 105 1 54 106 3 52 107 3 66 108 3 44 109 2 57 110 3 39 111 3 60 112 3 45 113 3 41 114 1 50 115 3 39 116 1 43 117 3 48 118 3 37 119 3 58 120 2 46 121 3 43 122 2 44 123 3 34 124 2 30 125 2 50 126 2 39 127 3 37 128 3 55 129 1 48 130 1 41 131 3 39 132 3 36 133 2 43 134 1 50 135 3 55 136 3 43 137 3 60 138 2 48 139 1 30 140 3 43 141 3 39 142 3 52 143 2 39 144 3 39 145 2 56 146 3 59 147 3 46 148 2 57 149 3 50 150 3 54 151 3 50 152 3 60 153 1 59 154 3 41 155 2 48 156 3 59 157 3 60 158 1 56 159 1 56 160 3 51
Names of X columns:
SUBJECTNO MOMAGE MC30VRB
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){ 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<-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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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