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Data X:
10 10 10 10 21 36 8 8 9 15 22 32 8 6 12 14 17 33 9 10 14 14 21 39 5 8 6 8 19 34 10 10 13 19 23 39 8 7 12 17 21 36 9 10 13 18 22 33 8 6 6 10 11 30 7 7 12 15 20 39 10 9 10 16 18 37 10 6 9 12 16 37 9 7 12 13 18 35 4 6 7 10 13 32 4 4 10 14 17 36 8 6 11 15 20 36 9 8 15 20 20 41 10 9 10 9 15 36 8 8 12 12 18 37 5 6 10 13 15 29 10 6 12 16 19 39 8 10 11 12 19 37 7 8 11 14 19 32 8 8 12 15 20 36 8 7 15 19 20 43 9 4 12 16 16 30 8 9 11 16 18 33 6 8 9 14 17 28 8 10 11 14 18 30 8 8 11 14 13 28 5 6 9 13 20 39 9 7 15 18 21 34 8 8 12 15 17 34 8 5 9 15 19 29 8 10 12 15 20 32 6 2 12 13 15 33 6 6 9 14 15 27 9 7 9 15 19 35 8 5 11 14 18 38 9 8 12 19 22 40 10 7 12 16 20 34 8 7 12 16 18 34 8 10 12 12 14 26 7 7 6 10 15 39 7 6 11 11 17 34 10 10 12 13 16 39 8 6 9 14 17 26 7 5 11 11 15 30 10 8 9 11 17 34 7 8 10 16 18 34 7 5 10 9 16 29 9 8 9 16 18 41 9 10 12 19 22 43 8 7 11 13 16 31 6 7 9 15 16 33 8 7 9 14 20 34 9 7 12 15 18 30 2 2 6 11 16 23 6 4 10 14 16 29 8 6 12 15 20 35 8 7 11 17 21 40 7 9 14 16 18 27 8 9 8 13 15 30 6 4 9 15 18 27 10 9 10 14 18 29 10 9 10 15 20 33 10 8 10 14 18 32 8 7 11 12 16 33 8 9 10 12 19 36 7 7 12 15 20 34 10 6 14 17 22 45 5 7 10 13 18 30 3 2 8 5 8 22 2 3 8 7 13 24 3 4 7 10 13 25 4 5 11 15 18 26 2 2 6 9 12 27 6 6 9 9 16 27 8 8 12 15 21 35 8 5 12 14 20 36 5 4 12 11 18 32 10 10 9 18 22 35 9 10 15 20 23 35 8 10 15 20 23 36 9 9 13 16 21 37 8 5 9 15 16 33 5 5 12 14 14 25 7 7 9 13 18 35 9 10 15 18 22 37 8 9 11 14 20 36 4 8 11 12 18 35 7 8 6 9 12 29 8 8 14 19 17 35 7 8 11 13 15 31 7 8 8 12 18 30 9 7 10 14 18 37 6 6 10 6 15 36 7 8 9 14 16 35 4 2 8 11 15 32 6 5 9 11 16 34 10 4 10 14 19 37 9 9 11 12 19 36 10 10 14 19 23 39 8 6 12 13 20 37 4 4 9 14 18 31 8 10 13 17 21 40 5 6 8 12 19 38 8 7 12 16 18 35 9 7 14 15 19 38 8 8 9 15 17 32 4 6 10 15 21 41 8 5 12 16 19 28 10 6 12 15 24 40 6 7 9 12 12 25 7 6 9 13 15 28 10 9 12 14 18 37 9 9 15 17 19 37 8 7 12 14 22 40 3 6 11 14 19 26 8 7 8 14 16 30 7 7 11 15 19 32 7 8 11 11 18 31 8 7 10 11 18 28 8 8 12 16 19 34 7 7 9 12 21 39 7 4 11 12 19 33 9 10 15 19 22 43 9 8 14 18 23 37 9 8 6 16 17 31 4 2 9 16 18 31 6 6 9 13 19 34 6 4 8 11 15 32 6 4 7 10 14 27 8 9 10 14 18 34 3 2 6 14 17 28 8 6 9 14 19 32 8 7 9 16 16 39 6 4 7 10 14 28 10 10 11 16 20 39 2 3 9 7 16 32 9 7 12 16 18 36 6 4 9 15 16 31 6 8 10 17 21 39 5 4 11 11 16 23 4 5 7 11 14 25 7 6 12 10 16 32 5 5 8 13 19 32 8 9 13 14 19 36 6 6 11 13 19 39 9 8 11 13 18 31 6 4 12 12 16 32 4 4 11 10 14 28 7 8 12 15 19 34 2 4 3 6 11 28 8 10 10 15 18 38 9 8 13 15 18 35 6 5 10 11 16 32 5 3 6 14 20 26 7 7 11 14 18 32 8 6 12 16 20 28 4 5 9 12 16 31 9 5 10 15 18 33 9 9 15 20 19 38 9 2 9 12 19 38 7 7 6 9 15 36 5 7 9 13 17 31 7 5 15 15 21 36 9 9 15 19 24 43 8 4 9 11 16 37 6 5 11 11 13 28 9 9 9 17 21 35 8 7 11 15 16 34 7 6 10 14 17 40 7 8 9 15 17 31 7 7 6 11 18 41 8 6 12 12 18 35 10 8 13 15 23 38 6 6 12 16 20 37 6 7 12 16 20 31
Names of X columns:
Intention_to_Use Relative_Advantage Perceived_Usefulness Perceived_Ease_of_Use Information_Quality System_Quality
Response Variable (column number)
Factor Variable (column number)
Include Intercept Term ?
0.96Pearson Chi-SquaredPearson Chi-SquaredExact Pearson Chi-Squared by SimulationTRUE300000FALSETRUE
TRUE
FALSE
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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){ '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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