R version 2.15.1 (2012-06-22) -- "Roasted Marshmallows"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
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+ ,dim=c(5
+ ,117)
+ ,dimnames=list(c('pre'
+ ,'post'
+ ,'treat'
+ ,'diff'
+ ,'gender')
+ ,1:117))
> y <- array(NA,dim=c(5,117),dimnames=list(c('pre','post','treat','diff','gender'),1:117))
> 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)
> par4 = 'TRUE'
> par3 = '5'
> par2 = '3'
> par1 = '4'
> ylab = 'Y Variable Name'
> xlab = 'X Variable Name'
> main = 'Title Goes Here'
> 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] "diff"
> (V2<-dimnames(y)[[1]][cat2])
[1] "treat"
> (V3 <-dimnames(y)[[1]][cat3])
[1] "gender"
> 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, data = xdf)
Coefficients:
(Intercept) Treatment_AF
0.47059 0.05882
Treatment_AH Treatment_B1
-0.47059 -0.17059
Treatment_AF:Treatment_B1 Treatment_AH:Treatment_B1
0.11944 0.20905
> (aov.xdf<-aov(lmxdf) )
Call:
aov(formula = lmxdf)
Terms:
Treatment_A Treatment_B Treatment_A:Treatment_B Residuals
Sum of Squares 4.852212 0.105118 0.201328 21.371257
Deg. of Freedom 2 1 2 111
Residual standard error: 0.4387868
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 4.8522 2.42611 12.6009 1.17e-05 ***
Treatment_B 1 0.1051 0.10512 0.5460 0.4615
Treatment_A:Treatment_B 2 0.2013 0.10066 0.5228 0.5943
Residuals 111 21.3713 0.19253
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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$coefficients[i], digits=3),,FALSE)
+ }
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/18shh1351643749.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, ' ',,TRUE)
> a<-table.element(a, 'Df',,FALSE)
> a<-table.element(a, 'Sum Sq',,FALSE)
> a<-table.element(a, 'Mean Sq',,FALSE)
> a<-table.element(a, 'F value',,FALSE)
> a<-table.element(a, 'Pr(>F)',,FALSE)
> a<-table.row.end(a)
> for(i in 1 : length(rownames(anova.xdf))-1){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(anova.xdf)[i] ,,TRUE)
+ a<-table.element(a, anova.xdf$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$'Mean Sq'[i+1], digits=3),,FALSE)
> a<-table.element(a, ' ',,FALSE)
> a<-table.element(a, ' ',,FALSE)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/2x4ki1351643749.tab")
> postscript(file="/var/fisher/rcomp/tmp/3o2af1351643749.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> boxplot(Response ~ Treatment_A + Treatment_B, data=xdf, xlab=V2, ylab=V1, main='Boxplots of ANOVA Groups')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/4h2o11351643749.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> xdf2 <- xdf # to preserve xdf make copy for function
> names(xdf2) <- c(V1, V2, V3)
> plot.design(xdf2, main='Design Plot of Group Means')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/5aiz11351643749.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> interaction.plot(xdf$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/fisher/rcomp/tmp/68fyw1351643749.ps",horizontal=F,onefile=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()
+ }
null device
1
> 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/fisher/rcomp/tmp/7fbtm1351643749.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/fisher/rcomp/tmp/8h9uc1351643749.tab")
+ }
> library(car)
Loading required package: MASS
Loading required package: nnet
> 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/fisher/rcomp/tmp/94yls1351643749.tab")
>
> try(system("convert tmp/3o2af1351643749.ps tmp/3o2af1351643749.png",intern=TRUE))
character(0)
> try(system("convert tmp/4h2o11351643749.ps tmp/4h2o11351643749.png",intern=TRUE))
character(0)
> try(system("convert tmp/5aiz11351643749.ps tmp/5aiz11351643749.png",intern=TRUE))
character(0)
> try(system("convert tmp/68fyw1351643749.ps tmp/68fyw1351643749.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.468 0.477 2.933