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Data X:
4512 'Man' '20-46' 3738 'Man' '20-46' 4261 'Man' '20-46' 3777 'Man' '20-46' 4177 'Man' '20-46' 3585 'Man' '20-46' 3785 'Man' '20-46' 3559 'Man' '20-46' 3613 'Man' '20-46' 3982 'Man' '20-46' 3443 'Man' '20-46' 3993 'Man' '20-46' 3640 'Man' '20-46' 4208 'Man' '20-46' 3832 'Man' '20-46' 3876 'Man' '20-46' 3497 'Man' '20-46' 3466 'Man' '20-46' 3095 'Man' '20-46' 4424 'Man' '20-46' 3878 'Man' '20-46' 4046 'Man' '20-46' 3804 'Man' '20-46' 3710 'Man' '20-46' 4747 'Man' '20-46' 4423 'Man' '20-46' 4036 'Man' '20-46' 4022 'Man' '20-46' 3454 'Man' '20-46' 4175 'Man' '20-46' 3787 'Man' '20-46' 3796 'Man' '20-46' 4103 'Man' '20-46' 4161 'Man' '20-46' 4158 'Man' '20-46' 3814 'Man' '20-46' 3527 'Man' '20-46' 3748 'Man' '20-46' 3334 'Man' '20-46' 3492 'Man' '20-46' 3962 'Man' '20-46' 3505 'Man' '20-46' 4315 'Man' '20-46' 3804 'Man' '20-46' 3863 'Man' '20-46' 4034 'Man' '20-46' 4308 'Man' '20-46' 3165 'Man' '20-46' 3641 'Man' '20-46' 3644 'Man' '20-46' 3891 'Man' '20-46' 3793 'Man' '20-46' 4270 'Man' '20-46' 4063 'Man' '20-46' 4012 'Man' '20-46' 3458 'Man' '20-46' 3890 'Man' '20-46' 4166 'Man' '46+' 3935 'Man' '46+' 3669 'Man' '46+' 3866 'Man' '46+' 3393 'Man' '46+' 4442 'Man' '46+' 4253 'Man' '46+' 3727 'Man' '46+' 3329 'Man' '46+' 3415 'Man' '46+' 3372 'Man' '46+' 4430 'Man' '46+' 4381 'Man' '46+' 4008 'Man' '46+' 3858 'Man' '46+' 4121 'Man' '46+' 4057 'Man' '46+' 3824 'Man' '46+' 3394 'Man' '46+' 3558 'Man' '46+' 3362 'Man' '46+' 3930 'Man' '46+' 3835 'Man' '46+' 3830 'Man' '46+' 3856 'Man' '46+' 3249 'Man' '46+' 3577 'Man' '46+' 3933 'Man' '46+' 3850 'Man' '46+' 3309 'Man' '46+' 3406 'Man' '46+' 3506 'Man' '46+' 3907 'Man' '46+' 4160 'Man' '46+' 3318 'Man' '46+' 3662 'Man' '46+' 3899 'Man' '46+' 3700 'Man' '46+' 3779 'Man' '46+' 3473 'Man' '46+' 3490 'Man' '46+' 3654 'Man' '46+' 3478 'Man' '46+' 3495 'Man' '46+' 3834 'Man' '46+' 3876 'Man' '46+' 3661 'Man' '46+' 3618 'Man' '46+' 3648 'Man' '46+' 4032 'Man' '46+' 3399 'Man' '46+' 3916 'Man' '46+' 4430 'Man' '46+' 3695 'Man' '46+' 3524 'Man' '46+' 3571 'Man' '46+' 3594 'Man' '46+' 3383 'Man' '46+' 3499 'Man' '46+' 3589 'Man' '46+' 3900 'Man' '46+' 4114 'Man' '46+' 3937 'Man' '46+' 3399 'Man' '46+' 4200 'Man' '46+' 4488 'Man' '46+' 3614 'Man' '46+' 4051 'Man' '46+' 3782 'Man' '46+' 3391 'Man' '46+' 3124 'Man' '46+' 4053 'Man' '46+' 3582 'Man' '46+' 3666 'Man' '46+' 3532 'Man' '46+' 4046 'Man' '46+' 3667 'Man' '46+' 2857 'Vrouw' '20-46' 3436 'Vrouw' '20-46' 3791 'Vrouw' '20-46' 3302 'Vrouw' '20-46' 3104 'Vrouw' '20-46' 3171 'Vrouw' '20-46' 3572 'Vrouw' '20-46' 3530 'Vrouw' '20-46' 3175 'Vrouw' '20-46' 3438 'Vrouw' '20-46' 3903 'Vrouw' '20-46' 3899 'Vrouw' '20-46' 3401 'Vrouw' '20-46' 3267 'Vrouw' '20-46' 3451 'Vrouw' '20-46' 3090 'Vrouw' '20-46' 3413 'Vrouw' '20-46' 3323 'Vrouw' '20-46' 3680 'Vrouw' '20-46' 3439 'Vrouw' '20-46' 3853 'Vrouw' '20-46' 3156 'Vrouw' '20-46' 3279 'Vrouw' '20-46' 3707 'Vrouw' '20-46' 4006 'Vrouw' '20-46' 3269 'Vrouw' '20-46' 3071 'Vrouw' '20-46' 3779 'Vrouw' '20-46' 3548 'Vrouw' '20-46' 3292 'Vrouw' '20-46' 3497 'Vrouw' '20-46' 3082 'Vrouw' '20-46' 3248 'Vrouw' '20-46' 3358 'Vrouw' '20-46' 3803 'Vrouw' '20-46' 3566 'Vrouw' '20-46' 3145 'Vrouw' '20-46' 3503 'Vrouw' '20-46' 3571 'Vrouw' '20-46' 3724 'Vrouw' '20-46' 3615 'Vrouw' '20-46' 3203 'Vrouw' '20-46' 3609 'Vrouw' '20-46' 3561 'Vrouw' '20-46' 3979 'Vrouw' '20-46' 3533 'Vrouw' '20-46' 3689 'Vrouw' '20-46' 3158 'Vrouw' '20-46' 4005 'Vrouw' '20-46' 3181 'Vrouw' '20-46' 3479 'Vrouw' '20-46' 3642 'Vrouw' '20-46' 3632 'Vrouw' '20-46' 3069 'Vrouw' '46+' 3394 'Vrouw' '46+' 3703 'Vrouw' '46+' 3165 'Vrouw' '46+' 3354 'Vrouw' '46+' 3000 'Vrouw' '46+' 3687 'Vrouw' '46+' 3556 'Vrouw' '46+' 2773 'Vrouw' '46+' 3058 'Vrouw' '46+' 3344 'Vrouw' '46+' 3493 'Vrouw' '46+' 3297 'Vrouw' '46+' 3360 'Vrouw' '46+' 3228 'Vrouw' '46+' 3277 'Vrouw' '46+' 3851 'Vrouw' '46+' 3067 'Vrouw' '46+' 3692 'Vrouw' '46+' 3402 'Vrouw' '46+' 3995 'Vrouw' '46+' 3318 'Vrouw' '46+' 2720 'Vrouw' '46+' 2937 'Vrouw' '46+' 3580 'Vrouw' '46+' 2939 'Vrouw' '46+' 2989 'Vrouw' '46+' 3586 'Vrouw' '46+' 3156 'Vrouw' '46+' 3246 'Vrouw' '46+' 3170 'Vrouw' '46+' 3268 'Vrouw' '46+' 3389 'Vrouw' '46+' 3381 'Vrouw' '46+' 2864 'Vrouw' '46+' 3740 'Vrouw' '46+' 3479 'Vrouw' '46+' 3647 'Vrouw' '46+' 3716 'Vrouw' '46+' 3284 'Vrouw' '46+' 4204 'Vrouw' '46+' 3735 'Vrouw' '46+' 3218 'Vrouw' '46+' 3685 'Vrouw' '46+' 3704 'Vrouw' '46+' 3214 'Vrouw' '46+' 3394 'Vrouw' '46+' 3233 'Vrouw' '46+' 3352 'Vrouw' '46+' 3391 'Vrouw' '46+'
Names of X columns:
Inhoudhersenen Geslacht leeftijd
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 <- 'TRUE' 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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