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Type 'q()' to quit R. > x <- array(list(0,0,1,0,0,0,0,0,0,0,0,1,0,0,1,1,1,1,0,0,0,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,1,0,0,1),dim=c(3,40),dimnames=list(c('A','B','C'),1:40)) > y <- array(NA,dim=c(3,40),dimnames=list(c('A','B','C'),1:40)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par4 = 'FALSE' > par3 = '3' > par2 = '2' > par1 = '1' > ylab = 'Y Variable Name' > xlab = 'X Variable Name' > main = 'Title Goes Here' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Dr. Ian E. Holliday > #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > cat1 <- as.numeric(par1) # > cat2<- as.numeric(par2) # > cat3 <- as.numeric(par3) > intercept<-as.logical(par4) > x <- t(x) > x1<-as.numeric(x[,cat1]) > f1<-as.character(x[,cat2]) > f2 <- as.character(x[,cat3]) > xdf<-data.frame(x1,f1, f2) > (V1<-dimnames(y)[[1]][cat1]) [1] "A" > (V2<-dimnames(y)[[1]][cat2]) [1] "B" > (V3 <-dimnames(y)[[1]][cat3]) [1] "C" > names(xdf)<-c('Response', 'Treatment_A', 'Treatment_B') > if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment_A * Treatment_B- 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment_A * Treatment_B, data = xdf) ) Call: lm(formula = Response ~ Treatment_A * Treatment_B - 1, data = xdf) Coefficients: Treatment_A0 Treatment_A1 -7.660e-18 5.000e-01 Treatment_B1 Treatment_A1:Treatment_B1 1.213e-17 NA > (aov.xdf<-aov(lmxdf) ) Call: aov(formula = lmxdf) Terms: Treatment_A Treatment_B Residuals Sum of Squares 0.5 0.0 0.5 Deg. of Freedom 2 1 37 Residual standard error: 0.1162476 1 out of 4 effects not estimable Estimated effects may be unbalanced > (anova.xdf<-anova(lmxdf) ) Analysis of Variance Table Response: Response Df Sum Sq Mean Sq F value Pr(>F) Treatment_A 2 0.50000 0.25000 18.5 2.697e-06 *** Treatment_B 1 1.301e-33 1.301e-33 9.624e-32 1 Residuals 37 0.50000 0.01351 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'ANOVA Model', length(lmxdf$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="/var/www/html/freestat/rcomp/tmp/1ualr1288626757.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="/var/www/html/freestat/rcomp/tmp/2fbkf1288626757.tab") > postscript(file="/var/www/html/freestat/rcomp/tmp/3fbkf1288626757.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > boxplot(Response ~ Treatment_A + Treatment_B, data=xdf, xlab=V2, ylab=V1, main='Boxplots of ANOVA Groups') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/482ji1288626757.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > 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() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/582ji1288626757.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > 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() null device 1 > if(intercept==TRUE){ + thsd<-TukeyHSD(aov.xdf) + names(thsd) <- c(V2, V3, paste(V2, ':', V3, sep='')) + postscript(file="/var/www/html/freestat/rcomp/tmp/682ji1288626757.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + 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="/var/www/html/freestat/rcomp/tmp/7muzr1288626757.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="/var/www/html/freestat/rcomp/tmp/8e3gb1288626757.tab") + } > library(car) > lt.lmxdf<-levene.test(lmxdf) Warning message: In anova.lm(lm(resp ~ group)) : ANOVA F-tests on an essentially perfect fit are unreliable > 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="/var/www/html/freestat/rcomp/tmp/904fh1288626757.tab") > > try(system("convert tmp/3fbkf1288626757.ps tmp/3fbkf1288626757.png",intern=TRUE)) character(0) > try(system("convert tmp/482ji1288626757.ps tmp/482ji1288626757.png",intern=TRUE)) character(0) > try(system("convert tmp/582ji1288626757.ps tmp/582ji1288626757.png",intern=TRUE)) character(0) > try(system("convert tmp/682ji1288626757.ps tmp/682ji1288626757.png",intern=TRUE)) convert: unable to open image `tmp/682ji1288626757.ps': No such file or directory. convert: missing an image filename `tmp/682ji1288626757.png'. character(0) > > > proc.time() user system elapsed 1.130 0.617 1.246