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Data X:
1 6 88 3 8 94 3 8 90 3 7 73 1 5 68 2 7 80 3 8 86 3 9 86 2 9 91 1 3 79 1 9 96 3 7 92 3 9 72 3 8 96 1 6 70 3 7 86 3 8 87 3 9 88 2 7 79 2 6 90 1 8 95 1 7 85 3 8 90 1 9 115 1 9 84 3 7 79 1 4 94 2 7 97 3 7 86 2 9 111 2 7 87 3 9 98 1 10 87 3 5 68 3 6 88 1 9 82 2 9 111 1 8 75 1 6 94 2 6 95 1 5 80 1 8 95 3 8 68 2 5 94 2 6 88 1 9 84 1 4 101 1 8 98 2 9 78 3 7 109 3 7 102 3 6 81 3 9 97 2 9 75 2 8 97 3 6 101 3 10 101 2 8 95 2 7 95 3 8 95 2 3 90 3 8 107 3 10 92 2 7 86 2 5 70 3 10 95 3 5 96 2 8 91 1 9 87 2 6 92 2 9 97 2 8 102 2 5 91 3 8 68 2 3 88 3 7 97 1 8 90 3 10 101 3 9 94 1 10 101 1 9 109 2 8 100 1 8 103 3 8 94 1 9 97 3 4 85 2 6 75 3 7 77 1 4 87 1 9 78 2 7 108 3 8 97 3 8 106 1 7 107 2 7 95 2 9 107 3 8 115 3 8 101 1 9 85 3 9 90 3 10 115 3 7 95 2 8 97 3 5 112 3 9 97 3 8 77 3 7 90 1 8 94 3 8 103 1 7 77 3 6 98 3 7 90 3 7 111 2 6 77 3 6 88 2 7 75 3 9 92 2 6 78 2 10 106 2 4 80 3 8 87 3 7 92 3 5 86 3 9 85 2 8 90 1 9 101 3 8 94 3 8 86 3 9 86 2 8 90 1 9 75 3 7 86 3 6 91 3 8 97 2 6 91 3 5 70 2 3 98 3 6 96 3 8 95 2 7 100 3 8 95 3 6 97 3 9 97 3 9 92 1 10 115 3 7 88 2 5 87 3 8 100 3 9 98 1 8 102 3 4 96
Names of X columns:
MOMAGE MWARM30 WISCRY7V
Response Variable (column number)


Factor Variable (column number)


Include Intercept Term ?


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')

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center
R Framework error message	Warning: there are blank lines in the 'Data X' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.
R Engine error message	Error in list(1, 6, 88, 3, 8, 94, 3, 8, 90, 3, 7, 73, 1, 5, 68, 2, 7, : argument 67 is empty Calls: array Execution halted