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Data X:
12.9 11 12.2 19 12.8 16 7.4 24 6.7 15 12.6 17 14.8 19 13.3 19 11.1 28 8.2 26 11.4 15 6.4 26 10.6 16 12 24 6.3 25 11.3 22 11.9 15 9.3 21 9.6 22 10 27 6.4 26 13.8 26 10.8 22 13.8 21 11.7 22 10.9 20 16.1 21 13.4 20 9.9 22 11.5 21 8.3 8 11.7 22 9 20 9.7 24 10.8 17 10.3 20 10.4 23 12.7 20 9.3 22 11.8 19 5.9 15 11.4 20 13 22 10.8 17 12.3 14 11.3 24 11.8 17 7.9 23 12.7 25 12.3 16 11.6 18 6.7 20 10.9 18 12.1 23 13.3 24 10.1 23 5.7 13 14.3 20 8 20 13.3 19 9.3 22 12.5 22 7.6 15 15.9 17 9.2 19 9.1 20 11.1 22 13 21 14.5 21 12.2 16 12.3 20 11.4 21 8.8 20 14.6 23 12.6 18 13 16 12.6 17 13.2 24 9.9 13 7.7 19 10.5 20 13.4 22 10.9 19 4.3 21 10.3 15 11.8 21 11.2 24 11.4 22 8.6 20 13.2 21 12.6 19 5.6 14 9.9 25 8.8 11 7.7 17 9 22 7.3 20 11.4 22 13.6 15 7.9 23 10.7 20 10.3 22 8.3 16 9.6 25 14.2 18 8.5 19 13.5 25 4.9 21 6.4 22 9.6 21 11.6 22 11.1 23 4.35 20 12.7 6 18.1 15 17.85 18 16.6 24 12.6 22 17.1 21 19.1 23 16.1 20 13.35 20 18.4 18 14.7 25 10.6 16 12.6 20 16.2 14 13.6 22 18.9 26 14.1 20 14.5 17 16.15 22 14.75 22 14.8 20 12.45 17 12.65 22 17.35 17 8.6 22 18.4 21 16.1 25 11.6 11 17.75 19 15.25 24 17.65 17 16.35 22 17.65 17 13.6 26 14.35 20 14.75 19 18.25 21 9.9 24 16 21 18.25 19 16.85 13 14.6 24 13.85 28 18.95 27 15.6 22 14.85 23 11.75 19 18.45 18 15.9 23 17.1 21 16.1 22 19.9 17 10.95 15 18.45 21 15.1 20 15 26 11.35 19 15.95 28 18.1 21 14.6 19 15.4 22 15.4 21 17.6 20 13.35 19 19.1 11 15.35 17 7.6 19 13.4 20 13.9 17 19.1 21 15.25 21 12.9 12 16.1 23 17.35 22 13.15 22 12.15 21 12.6 20 10.35 18 15.4 21 9.6 24 18.2 22 13.6 20 14.85 17 14.75 19 14.1 16 14.9 19 16.25 23 19.25 8 13.6 22 13.6 23 15.65 15 12.75 17 14.6 21 9.85 25 12.65 18 19.2 20 16.6 21 11.2 21 15.25 24 11.9 22 13.2 22 16.35 23 12.4 17 15.85 15 18.15 22 11.15 19 15.65 18 17.75 21 7.65 20 12.35 19 15.6 19 19.3 16 15.2 18 17.1 23 15.6 22 18.4 23 19.05 20 18.55 24 19.1 25 13.1 25 12.85 20 9.5 23 4.5 21 11.85 23 13.6 23 11.7 11 12.4 21 13.35 27 11.4 19 14.9 21 19.9 16 11.2 21 14.6 22 17.6 16 14.05 18 16.1 23 13.35 24 11.85 20 11.95 20 14.75 18 15.15 4 13.2 14 16.85 22 7.85 17 7.7 23 12.6 20 7.85 18 10.95 19 12.35 20 9.95 15 14.9 24 16.65 21 13.4 19 13.95 19 15.7 27 16.85 23 10.95 23 15.35 20 12.2 17 15.1 21 17.75 23 15.2 22 14.6 16 16.65 20 8.1 16
Names of X columns:
TOT AMS.I1
Response Variable (column number)
Explanatory Variable (column number)
Include Intercept Term ?
TRUE
TRUE
FALSE
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R Code
par3 <- 'TRUE' par2 <- '1' par1 <- '2' 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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