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Data X:
36 67 1 36 86 2 56 86 2 48 103 3 32 74 1 44 63 1 39 82 2 34 93 2 41 77 1 50 111 3 39 71 1 62 103 3 52 89 2 37 75 1 50 88 2 41 84 2 55 85 2 41 70 1 56 104 3 39 88 2 52 77 1 46 77 1 44 72 1 48 70 1 41 83 2 50 110 3 50 91 2 44 80 2 52 91 2 54 86 2 44 85 2 52 107 3 37 93 2 52 87 2 50 84 2 36 73 1 50 84 2 52 86 2 55 99 3 31 75 1 36 87 2 49 79 1 42 82 2 37 95 3 41 84 2 30 85 2 52 95 3 30 63 1 41 78 1 44 85 2 66 86 2 48 75 1 43 98 3 57 71 1 46 63 1 54 71 1 48 84 2 48 81 2 52 93 2 62 79 1 58 63 1 58 93 2 62 92 2 48 93 2 46 83 2 34 80 2 66 111 3 52 92 2 55 79 1 55 69 1 57 83 2 56 80 2 55 91 2 56 97 3 54 85 2 55 85 2 46 99 3 52 67 1 32 87 2 44 68 1 46 81 2 59 80 2 46 93 2 46 93 2 54 102 3 66 104 3 56 90 2 59 85 2 57 92 2 52 82 2 48 85 2 44 89 2 41 77 1 50 79 1 48 76 1 48 101 3 59 81 2 34 92 2 46 89 2 54 81 2 55 77 1 54 95 3 59 85 2 44 81 2 54 76 1 52 93 2 66 104 3 44 89 2 57 76 1 39 77 1 60 71 1 45 79 1 41 89 2 50 81 2 39 99 3 43 81 2 48 84 2 37 85 2 58 111 3 46 78 1 43 111 3 44 78 1 34 87 2 30 92 2 50 93 2 39 70 1 37 84 2 55 75 1 48 105 3 41 96 3 39 85 2 36 87 2 43 75 1 50 103 3 55 86 2 43 77 1 60 74 1 48 74 1 30 76 1 43 83 2 39 101 3 52 83 2 39 92 2 39 74 1 56 87 2 59 71 1 46 79 1 57 83 2 50 80 2 54 90 2 50 80 2 60 96 3 59 109 3 41 98 3 48 85 2 59 83 2 60 86 2 56 72 1 56 83 2 51 75 1
Names of X columns:
verbalIQ maternalIQ MaternalIQgroup
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
par3 <- 'TRUE' par2 <- '3' par1 <- '1' 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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