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Data X:
888 63031 51 256 545 66751 24 160 186 7176 17 70 1405 78306 66 360 2047 137944 85 721 3617 260469 128 935 843 68781 34 287 643 80226 32 149 1181 73226 33 311 1835 178519 64 617 855 66476 35 262 1245 98606 46 385 993 50001 69 369 1684 91093 60 558 741 73884 24 220 854 72377 38 313 948 69388 33 229 331 15629 20 88 1602 71693 54 494 510 19896 16 153 628 39403 37 234 1279 99933 51 361 767 56088 28 280 1155 62006 31 331 1120 81665 51 378 622 65223 12 227 1203 88794 98 396 745 90642 53 179 1535 203699 61 509 1234 99340 25 504 757 56695 28 225 1087 108143 23 366 1105 58313 60 341 592 29101 40 171 1305 113060 29 437 0 0 0 0 705 65773 33 313 1188 67047 34 366 1110 41953 21 232 1094 109835 35 389 1061 82577 33 340 748 59588 26 316 404 40064 12 140 1076 70227 45 419 673 60437 29 226 516 47000 35 161 354 40295 13 103 1011 103397 54 356 890 78982 39 293 1066 60206 27 414 518 39887 21 156 696 49791 35 189 1095 129283 44 442 928 104816 44 321 1008 101395 33 367 951 72824 30 309 770 75328 25 232 438 33891 11 137 568 62164 37 194 614 28266 24 220 499 35093 21 149 823 35252 34 306 540 36977 19 178 475 42406 18 145 433 56353 12 144 818 58817 23 270 1173 76053 43 301 1719 70872 48 501 549 42372 20 153 110 15428 11 31 1594 114177 73 500 622 53544 26 199 656 51379 33 242 920 40756 39 265 833 46357 20 293 497 17799 20 141 864 71154 30 234 994 58305 38 336 443 27454 16 124 615 34323 34 241 524 44761 32 127 899 113862 27 327 556 35027 16 175 896 62396 22 331 515 29613 25 176 894 65559 28 281 1313 109788 108 291 475 26263 27 131 446 39773 23 148 639 53398 22 194 795 56435 23 300 1243 77283 45 370 558 71738 29 187 573 48096 29 210 439 25214 22 185 1307 119332 63 445 765 79201 27 234 222 19349 11 67 935 73984 53 300 821 54133 35 336 317 21623 16 116 425 25497 11 141 711 69535 38 236 363 30709 21 98 427 37043 23 97 463 24716 13 152 545 54865 16 132 368 27246 18 97 0 0 0 0 596 38814 13 165 478 27646 31 153 713 65373 18 226 639 43021 34 182 477 43116 40 172 38 3058 4 1 0 0 0 0 592 96347 24 196 665 45666 27 260 1007 68923 49 291 495 45266 22 183 778 43410 19 292 875 83842 34 257 490 39296 21 141 682 35223 23 189 484 39841 18 129 285 19764 12 75 934 59975 20 301 553 64589 15 204 753 63339 14 257 256 11796 9 79 80 7627 8 25 618 68998 30 217 41 6836 3 11 497 28834 14 209 42 5118 3 6 347 20898 13 115 0 0 0 0 441 42690 18 167 281 14507 11 75 81 7131 4 27 61 4194 11 14 313 21416 9 96 326 30591 12 95 553 42419 9 228
Names of X columns:
pageviews time logins compendiumviews
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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