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Type 'q()' to quit R. > x <- array(list('WWE' + ,0 + ,'WWE' + ,0 + ,'WWE' + ,1 + ,'WWE' + ,0 + ,'WWE' + ,1 + ,'WWE' + ,1 + ,'WWE' + ,0 + ,'WWE' + ,1 + ,'WWE' + ,0 + ,'WWE' + ,0 + ,'WWE' + ,0 + ,'WWE' + ,0 + ,'WWE' + ,0 + ,'WWE' + ,NA + ,'WWE' + ,1 + ,'WWE' + ,NA + ,'WWE' + ,-1 + ,'WWE' + ,0 + ,'WWE' + ,1 + ,'WWE' + ,0 + ,'WWE' + ,0 + ,'WWE' + ,-1 + ,'WWE' + ,0 + ,'WWE' + ,0 + ,'WWE' + ,1 + ,'WWE' + ,1 + ,'WWE' + ,0 + ,'WWE' + ,-1 + ,'WWE' + ,0 + ,'WWE' + ,0 + ,'WWE' + ,1 + ,'WWE' + ,0 + ,'WWE' + ,0 + ,'WWE' + ,0 + ,'WWE' + ,0 + ,'WWE' + ,-1 + ,'WWE' + ,-1 + ,'WWE' + ,0 + ,'WWE' + ,NA + ,'WWE' + ,1 + ,'WWE' + ,0 + ,'CSWE' + ,0 + ,'CSWE' + ,NA + ,'CSWE' + ,0 + ,'CSWE' + ,NA + ,'CSWE' + ,0 + ,'CSWE' + ,0 + ,'CSWE' + ,0 + ,'CSWE' + ,1 + ,'CSWE' + ,0 + ,'CSWE' + ,-1 + ,'CSWE' + ,1 + ,'CSWE' + ,0 + ,'CSWE' + ,0 + ,'CSWE' + ,NA + ,'CSWE' + ,0 + ,'CSWE' + ,NA + ,'CSWE' + ,-1 + ,'CSWE' + ,0 + ,'CSWE' + ,NA + ,'CSWE' + ,0 + ,'CSWE' + ,0 + ,'CSWE' + ,NA + ,'CSWE' + ,0 + ,'CSWE' + ,0 + ,'CSWE' + ,0 + ,'CSWE' + ,1 + ,'CSWE' + ,0 + ,'CSWE' + ,0 + ,'CSWE' + ,-1 + ,'CSWE' + ,1 + ,'CSWE' + ,1 + ,'CSWE' + ,0 + ,'CSWE' + ,NA + ,'CSWE' + ,0 + ,'CSWE' + ,NA + ,'CSWE' + ,0 + ,'CSWE' + ,0 + ,'CSWE' + ,0 + ,'CSWE' + ,0 + ,'CSWE' + ,0 + ,'C' + ,0 + ,'C' + ,1 + ,'C' + ,-1 + ,'C' + ,1 + ,'C' + ,NA + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,-1 + ,'C' + ,NA + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,NA + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,-1 + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,-1 + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,-1 + ,'C' + ,1 + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,0 + ,'C' + ,1 + ,'C' + ,0 + ,'C' + ,NA + ,'C' + ,-1) + ,dim=c(2 + ,120) + ,dimnames=list(c('Treatment' + ,'Post2-pre') + ,1:120)) > y <- array(NA,dim=c(2,120),dimnames=list(c('Treatment','Post2-pre'),1:120)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } There were 50 or more warnings (use warnings() to see the first 50) > par3 = 'TRUE' > par2 = '1' > par1 = '2' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > cat1 <- as.numeric(par1) # > cat2<- as.numeric(par2) # > intercept<-as.logical(par3) > x <- t(x) > x1<-as.numeric(x[,cat1]) > f1<-as.character(x[,cat2]) > xdf<-data.frame(x1,f1) > (V1<-dimnames(y)[[1]][cat1]) [1] "Post2-pre" > (V2<-dimnames(y)[[1]][cat2]) [1] "Treatment" > names(xdf)<-c('Response', 'Treatment') > if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, data = xdf) ) Call: lm(formula = Response ~ Treatment, data = xdf) Coefficients: (Intercept) TreatmentCSWE TreatmentWWE -0.05714 0.11964 0.18872 > (aov.xdf<-aov(lmxdf) ) Call: aov(formula = lmxdf) Terms: Treatment Residuals Sum of Squares 0.65909 32.10282 Deg. of Freedom 2 102 Residual standard error: 0.5610112 Estimated effects may be unbalanced 15 observations deleted due to missingness > (anova.xdf<-anova(lmxdf) ) Analysis of Variance Table Response: Response Df Sum Sq Mean Sq F value Pr(>F) Treatment 2 0.659 0.32954 1.0471 0.3547 Residuals 102 32.103 0.31473 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'ANOVA Model', length(lmxdf$coefficients)+1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 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$coefficients[i], digits=3),,FALSE) + } > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/1umc71321010472.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'ANOVA Statistics', 5+1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, ' ',,TRUE) > a<-table.element(a, 'Df',,FALSE) > a<-table.element(a, 'Sum Sq',,FALSE) > a<-table.element(a, 'Mean Sq',,FALSE) > a<-table.element(a, 'F value',,FALSE) > a<-table.element(a, 'Pr(>F)',,FALSE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, V2,,TRUE) > a<-table.element(a, anova.xdf$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="/var/wessaorg/rcomp/tmp/2dllb1321010472.tab") > postscript(file="/var/wessaorg/rcomp/tmp/3ex321321010472.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > boxplot(Response ~ Treatment, data=xdf, xlab=V2, ylab=V1) > dev.off() null device 1 > if(intercept==TRUE){ + thsd<-TukeyHSD(aov.xdf) + postscript(file="/var/wessaorg/rcomp/tmp/440fb1321010472.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(thsd) + dev.off() + } null device 1 > 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="/var/wessaorg/rcomp/tmp/51syd1321010472.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="/var/wessaorg/rcomp/tmp/6nu4u1321010472.tab") + } > library(car) Loading required package: MASS Loading required package: nnet Loading required package: survival Loading required package: splines > lt.lmxdf<-levene.test(lmxdf) Warning message: 'levene.test' is deprecated. Use 'leveneTest' instead. See help("Deprecated") and help("car-deprecated"). > 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/wessaorg/rcomp/tmp/74vzb1321010472.tab") > > try(system("convert tmp/3ex321321010472.ps tmp/3ex321321010472.png",intern=TRUE)) character(0) > try(system("convert tmp/440fb1321010472.ps tmp/440fb1321010472.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.879 0.125 1.036