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Data X:
13 41 38 16 39 32 19 30 35 15 31 33 14 34 37 13 35 29 19 39 31 15 34 36 14 36 35 15 37 38 16 38 31 16 36 34 16 38 35 16 39 38 17 33 37 15 32 33 15 36 32 20 38 38 18 39 38 16 32 32 16 32 33 16 31 31 19 39 38 16 37 39 17 39 32 17 41 32 16 36 35 15 33 37 16 33 33 14 34 33 15 31 28 12 27 32 14 37 31 16 34 37 14 34 30 7 32 33 10 29 31 14 36 33 16 29 31 16 35 33 16 37 32 14 34 33 20 38 32 14 35 33 14 38 28 11 37 35 14 38 39 15 33 34 16 36 38 14 38 32 16 32 38 14 32 30 12 32 33 16 34 38 9 32 32 14 37 32 16 39 34 16 29 34 15 37 36 16 35 34 12 30 28 16 38 34 16 34 35 14 31 35 16 34 31 17 35 37 18 36 35 18 30 27 12 39 40 16 35 37 10 38 36 14 31 38 18 34 39 18 38 41 16 34 27 17 39 30 16 37 37 16 34 31 13 28 31 16 37 27 16 33 36 20 37 38 16 35 37 15 37 33 15 32 34 16 33 31 14 38 39 16 33 34 16 29 32 15 33 33 12 31 36 17 36 32 16 35 41 15 32 28 13 29 30 16 39 36 16 37 35 16 35 31 16 37 34 14 32 36 16 38 36 16 37 35 20 36 37 15 32 28 16 33 39 13 40 32 17 38 35 16 41 39 16 36 35 12 43 42 16 30 34 16 31 33 17 32 41 13 32 33 12 37 34 18 37 32 14 33 40 14 34 40 13 33 35 16 38 36 13 33 37 16 31 27 13 38 39 16 37 38 15 33 31 16 31 33 15 39 32 17 44 39 15 33 36 12 35 33 16 32 33 10 28 32 16 40 37 12 27 30 14 37 38 15 32 29 13 28 22 15 34 35 11 30 35 12 35 34 8 31 35 16 32 34 15 30 34 17 30 35 16 31 23 10 40 31 18 32 27 13 36 36 16 32 31 13 35 32 10 38 39 15 42 37 16 34 38 16 35 39 14 35 34 10 33 31 17 36 32 13 32 37 15 33 36 16 34 32 12 32 35 13 34 36
Names of X columns:
Learning-score Connected Separate
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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