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Data X:
1530 1 1 1297 1 1 1335 1 1 1282 1 1 1590 1 1 1300 1 1 1400 1 1 1255 1 1 1355 1 1 1375 1 1 1340 1 1 1380 1 1 1355 1 1 1522 1 1 1208 1 1 1405 1 1 1358 1 1 1292 1 1 1340 1 1 1400 1 1 1357 1 1 1287 1 1 1275 1 1 1270 1 1 1635 1 1 1505 1 1 1490 1 1 1485 1 1 1310 1 1 1420 1 1 1318 1 1 1432 1 1 1364 1 1 1405 1 1 1432 1 1 1207 1 1 1375 1 1 1350 1 1 1236 1 1 1250 1 1 1350 1 1 1320 1 1 1525 1 1 1570 1 1 1340 1 1 1422 1 1 1506 1 1 1215 1 1 1311 1 1 1300 1 1 1224 1 1 1350 1 1 1335 1 1 1390 1 1 1400 1 1 1225 1 1 1310 1 1 1560 1 2 1330 1 2 1222 1 2 1415 1 2 1175 1 2 1330 1 2 1485 1 2 1470 1 2 1135 1 2 1310 1 2 1154 1 2 1510 1 2 1415 1 2 1468 1 2 1390 1 2 1380 1 2 1432 1 2 1240 1 2 1195 1 2 1225 1 2 1188 1 2 1252 1 2 1315 1 2 1245 1 2 1430 1 2 1279 1 2 1245 1 2 1309 1 2 1412 1 2 1120 1 2 1220 1 2 1280 1 2 1440 1 2 1370 1 2 1192 1 2 1230 1 2 1346 1 2 1290 1 2 1165 1 2 1240 1 2 1132 1 2 1242 1 2 1270 1 2 1218 1 2 1430 1 2 1588 1 2 1320 1 2 1290 1 2 1260 1 2 1425 1 2 1226 1 2 1360 1 2 1620 1 2 1310 1 2 1250 1 2 1295 1 2 1290 1 2 1290 1 2 1275 1 2 1250 1 2 1270 1 2 1362 1 2 1300 1 2 1173 1 2 1256 1 2 1440 1 2 1180 1 2 1306 1 2 1350 1 2 1125 1 2 1165 1 2 1312 1 2 1300 1 2 1270 1 2 1335 1 2 1450 1 2 1310 1 2 1027 2 1 1235 2 1 1260 2 1 1165 2 1 1080 2 1 1127 2 1 1270 2 1 1252 2 1 1200 2 1 1290 2 1 1334 2 1 1380 2 1 1140 2 1 1243 2 1 1340 2 1 1168 2 1 1322 2 1 1249 2 1 1321 2 1 1192 2 1 1373 2 1 1170 2 1 1265 2 1 1235 2 1 1302 2 1 1241 2 1 1078 2 1 1520 2 1 1460 2 1 1075 2 1 1280 2 1 1180 2 1 1250 2 1 1190 2 1 1374 2 1 1306 2 1 1202 2 1 1240 2 1 1316 2 1 1280 2 1 1350 2 1 1180 2 1 1210 2 1 1127 2 1 1324 2 1 1210 2 1 1290 2 1 1100 2 1 1280 2 1 1175 2 1 1160 2 1 1205 2 1 1163 2 1 1022 2 2 1243 2 2 1350 2 2 1237 2 2 1204 2 2 1090 2 2 1355 2 2 1250 2 2 1076 2 2 1120 2 2 1220 2 2 1240 2 2 1220 2 2 1095 2 2 1235 2 2 1105 2 2 1405 2 2 1150 2 2 1305 2 2 1220 2 2 1296 2 2 1175 2 2 955 2 2 1070 2 2 1320 2 2 1060 2 2 1130 2 2 1250 2 2 1225 2 2 1180 2 2 1178 2 2 1142 2 2 1130 2 2 1185 2 2 1012 2 2 1280 2 2 1103 2 2 1408 2 2 1300 2 2 1246 2 2 1380 2 2 1350 2 2 1060 2 2 1350 2 2 1220 2 2 1110 2 2 1215 2 2 1104 2 2 1170 2 2 1120 2 2
Names of X columns:
Brain Gender Age
Response : Variable 1
Factor : Variable 2
Factor : Variable 3
Include Intercept Term ?
TRUE
TRUE
FALSE
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
par4 <- 'FALSE' par3 <- '3' par2 <- '2' par1 <- '1' 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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