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Data X:
11 12.9 19 12.2 16 12.8 24 7.4 15 6.7 17 12.6 19 14.8 19 13.3 28 11.1 26 8.2 15 11.4 26 6.4 16 10.6 24 12 25 6.3 22 11.3 15 11.9 21 9.3 22 9.6 27 10 26 6.4 26 13.8 22 10.8 21 13.8 22 11.7 20 10.9 21 16.1 20 13.4 22 9.9 21 11.5 8 8.3 22 11.7 20 9 24 9.7 17 10.8 20 10.3 23 10.4 20 12.7 22 9.3 19 11.8 15 5.9 20 11.4 22 13 17 10.8 14 12.3 24 11.3 17 11.8 23 7.9 25 12.7 16 12.3 18 11.6 20 6.7 18 10.9 23 12.1 24 13.3 23 10.1 13 5.7 20 14.3 20 8 19 13.3 22 9.3 22 12.5 15 7.6 17 15.9 19 9.2 20 9.1 22 11.1 21 13 21 14.5 16 12.2 20 12.3 21 11.4 20 8.8 23 14.6 18 12.6 16 13 17 12.6 24 13.2 13 9.9 19 7.7 20 10.5 22 13.4 19 10.9 21 4.3 15 10.3 21 11.8 24 11.2 22 11.4 20 8.6 21 13.2 19 12.6 14 5.6 25 9.9 11 8.8 17 7.7 22 9 20 7.3 22 11.4 15 13.6 23 7.9 20 10.7 22 10.3 16 8.3 25 9.6 18 14.2 19 8.5 25 13.5 21 4.9 22 6.4 21 9.6 22 11.6 23 11.1 20 4.35 6 12.7 15 18.1 18 17.85 24 16.6 22 12.6 21 17.1 23 19.1 20 16.1 20 13.35 18 18.4 25 14.7 16 10.6 20 12.6 14 16.2 22 13.6 26 18.9 20 14.1 17 14.5 22 16.15 22 14.75 20 14.8 17 12.45 22 12.65 17 17.35 22 8.6 21 18.4 25 16.1 11 11.6 19 17.75 24 15.25 17 17.65 22 16.35 17 17.65 26 13.6 20 14.35 19 14.75 21 18.25 24 9.9 21 16 19 18.25 13 16.85 24 14.6 28 13.85 27 18.95 22 15.6 23 14.85 19 11.75 18 18.45 23 15.9 21 17.1 22 16.1 17 19.9 15 10.95 21 18.45 20 15.1 26 15 19 11.35 28 15.95 21 18.1 19 14.6 22 15.4 21 15.4 20 17.6 19 13.35 11 19.1 17 15.35 19 7.6 20 13.4 17 13.9 21 19.1 21 15.25 12 12.9 23 16.1 22 17.35 22 13.15 21 12.15 20 12.6 18 10.35 21 15.4 24 9.6 22 18.2 20 13.6 17 14.85 19 14.75 16 14.1 19 14.9 23 16.25 8 19.25 22 13.6 23 13.6 15 15.65 17 12.75 21 14.6 25 9.85 18 12.65 20 19.2 21 16.6 21 11.2 24 15.25 22 11.9 22 13.2 23 16.35 17 12.4 15 15.85 22 18.15 19 11.15 18 15.65 21 17.75 20 7.65 19 12.35 19 15.6 16 19.3 18 15.2 23 17.1 22 15.6 23 18.4 20 19.05 24 18.55 25 19.1 25 13.1 20 12.85 23 9.5 21 4.5 23 11.85 23 13.6 11 11.7 21 12.4 27 13.35 19 11.4 21 14.9 16 19.9 21 11.2 22 14.6 16 17.6 18 14.05 23 16.1 24 13.35 20 11.85 20 11.95 18 14.75 4 15.15 14 13.2 22 16.85 17 7.85 23 7.7 20 12.6 18 7.85 19 10.95 20 12.35 15 9.95 24 14.9 21 16.65 19 13.4 19 13.95 27 15.7 23 16.85 23 10.95 20 15.35 17 12.2 21 15.1 23 17.75 22 15.2 16 14.6 20 16.65 16 8.1
Names of X columns:
AMS.I1 TOT
Response Variable (column number)
Explanatory Variable (column number)
Include Intercept Term ?
95
TRUE
FALSE
Chart options
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Label y-axis:
Label x-axis:
R Code
library(boot) cat1 <- as.numeric(par1) cat2<- as.numeric(par2) intercept<-as.logical(par3) x <- na.omit(t(x)) rsq <- function(formula, data, indices) { d <- data[indices,] # allows boot to select sample fit <- lm(formula, data=d) return(summary(fit)$r.square) } xdf<-data.frame(na.omit(t(y))) (V1<-dimnames(y)[[1]][cat1]) (V2<-dimnames(y)[[1]][cat2]) xdf <- data.frame(xdf[[cat1]], xdf[[cat2]]) names(xdf)<-c('Y', 'X') if(intercept == FALSE) (lmxdf<-lm(Y~ X - 1, data = xdf) ) else (lmxdf<-lm(Y~ X, data = xdf) ) (results <- boot(data=xdf, statistic=rsq, R=1000, formula=Y~X)) sumlmxdf<-summary(lmxdf) (aov.xdf<-aov(lmxdf) ) (anova.xdf<-anova(lmxdf) ) load(file='createtable') a<-table.start() nc <- ncol(sumlmxdf$'coefficients') nr <- nrow(sumlmxdf$'coefficients') a<-table.row.start(a) a<-table.element(a,'Linear Regression Model', nc+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, lmxdf$call['formula'],nc+1) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'coefficients:',1,TRUE) a<-table.element(a, ' ',nc,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, ' ',1,TRUE) for(i in 1 : nc){ a<-table.element(a, dimnames(sumlmxdf$'coefficients')[[2]][i],1,TRUE) }#end header a<-table.row.end(a) for(i in 1: nr){ a<-table.element(a,dimnames(sumlmxdf$'coefficients')[[1]][i] ,1,TRUE) for(j in 1 : nc){ a<-table.element(a, round(sumlmxdf$coefficients[i, j], digits=3), 1 ,FALSE) } a<-table.row.end(a) } a<-table.row.start(a) a<-table.element(a, '- - - ',1,TRUE) a<-table.element(a, ' ',nc,FALSE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Residual Std. Err. ',1,TRUE) a<-table.element(a, paste(round(sumlmxdf$'sigma', digits=3), ' on ', sumlmxdf$'df'[2], 'df') ,nc, FALSE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Multiple R-sq. ',1,TRUE) a<-table.element(a, round(sumlmxdf$'r.squared', digits=3) ,nc, FALSE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, '95% CI Multiple R-sq. ',1,TRUE) a<-table.element(a, paste('[',round(boot.ci(results,type='bca')$bca[1,4], digits=3),', ', round(boot.ci(results,type='bca')$bca[1,5], digits=3), ']',sep='') ,nc, FALSE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Adjusted R-sq. ',1,TRUE) a<-table.element(a, round(sumlmxdf$'adj.r.squared', digits=3) ,nc, FALSE) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'ANOVA Statistics', 5+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, ' ',1,TRUE) a<-table.element(a, 'Df',1,TRUE) a<-table.element(a, 'Sum Sq',1,TRUE) a<-table.element(a, 'Mean Sq',1,TRUE) a<-table.element(a, 'F value',1,TRUE) a<-table.element(a, 'Pr(>F)',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, V2,1,TRUE) a<-table.element(a, anova.xdf$Df[1]) a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3)) a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3)) a<-table.element(a, round(anova.xdf$'F value'[1], digits=3)) a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Residuals',1,TRUE) a<-table.element(a, anova.xdf$Df[2]) a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3)) a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3)) a<-table.element(a, ' ') a<-table.element(a, ' ') a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') bitmap(file='regressionplot.png') plot(Y~ X, data=xdf, xlab=V2, ylab=V1, main='Regression Solution') if(intercept == TRUE) abline(coef(lmxdf), col='red') if(intercept == FALSE) abline(0.0, coef(lmxdf), col='red') dev.off() library(car) bitmap(file='residualsQQplot.png') qqPlot(resid(lmxdf), main='QQplot of Residuals of Fit') dev.off() bitmap(file='residualsplot.png') plot(xdf$X, resid(lmxdf), main='Scatterplot of Residuals of Model Fit') dev.off() bitmap(file='cooksDistanceLmplot.png') plot(lmxdf, which=4) dev.off()
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