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Type 'q()' to quit R. > x <- array(list(37,21,20,25,85,38,25,48,43,18,19,22,68,37,27,49,30,12,18,15,57,33,23,37,87,38,29,60,15,35,22,30,72,41,36,55,40,35,21,27,60,34,20,47,54,29,26,43,79,31,35,50,56,32,28,45,35,25,29,27,53,28,24,39,75,39,31,52,70,35,26,53,79,31,24,60,31,42,19,20,17,40,22,32,82,41,31,58,59,40,27,41,26,25,15,17,54,39,24,33,27,19,19,20,62,45,29,44,79,47,28,56,26,30,10,18,69,33,29,59),dim=c(4,30),dimnames=list(c('SocSup','Temp','HomeEnv','Devel'),1:30)) > y <- array(NA,dim=c(4,30),dimnames=list(c('SocSup','Temp','HomeEnv','Devel'),1:30)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'TRUE' > par2 = '2' > par1 = '1' > ylab = 'Y Variable Name' > xlab = 'X Variable Name' > main = 'Title Goes Here' > par3 <- 'TRUE' > par2 <- '2' > par1 <- '1' > #'GNU S' R Code compiled by R2WASP v. 1.2.291 () > #Author: aston2 > #To cite this work: Ian E. Holliday, 2012, Simple Linear Regression (v1.0.5) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/Ian.Holliday/rwasp_Simple%20Regression%20Y%20~%20X.wasp/ > #Source of accompanying publication: > # > cat1 <- as.numeric(par1) > cat2<- as.numeric(par2) > intercept<-as.logical(par3) > x <- t(x) > xdf<-data.frame(t(y)) > (V1<-dimnames(y)[[1]][cat1]) [1] "SocSup" > (V2<-dimnames(y)[[1]][cat2]) [1] "Temp" > xdf <- data.frame(xdf[[cat1]], xdf[[cat2]]) > names(xdf)<-c('Y', 'X') > if(intercept == FALSE) (lmxdf<-lm(Y~ X - 1, data = xdf) ) else (lmxdf<-lm(Y~ X, data = xdf) ) Call: lm(formula = Y ~ X, data = xdf) Coefficients: (Intercept) X 13.824 1.221 > sumlmxdf<-summary(lmxdf) > (aov.xdf<-aov(lmxdf) ) Call: aov(formula = lmxdf) Terms: X Residuals Sum of Squares 2966.975 10580.391 Deg. of Freedom 1 28 Residual standard error: 19.43891 Estimated effects may be unbalanced > (anova.xdf<-anova(lmxdf) ) Analysis of Variance Table Response: Y Df Sum Sq Mean Sq F value Pr(>F) X 1 2967 2966.98 7.8518 0.009109 ** Residuals 28 10580 377.87 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > nc <- ncol(sumlmxdf$'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, 'Adjusted R-sq. ',1,TRUE) > a<-table.element(a, round(sumlmxdf$'adj.r.squared', digits=3) ,nc, FALSE) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/16p2y1393364019.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'ANOVA Statistics', 5+1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, ' ',1,TRUE) > a<-table.element(a, 'Df',1,TRUE) > a<-table.element(a, 'Sum Sq',1,TRUE) > a<-table.element(a, 'Mean Sq',1,TRUE) > a<-table.element(a, 'F value',1,TRUE) > a<-table.element(a, 'Pr(>F)',1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, V2,1,TRUE) > a<-table.element(a, anova.xdf$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$'Mean Sq'[2], digits=3)) > a<-table.element(a, ' ') > a<-table.element(a, ' ') > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/23k711393364019.tab") > postscript(file="/var/wessaorg/rcomp/tmp/3yypx1393364019.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(Y~ X, data=xdf, xlab=V2, ylab=V1, main='Regression Solution') > if(intercept == TRUE) abline(coef(lmxdf), col='red') > if(intercept == FALSE) abline(0.0, coef(lmxdf), col='red') > dev.off() null device 1 > library(car) Loading required package: MASS Loading required package: nnet > postscript(file="/var/wessaorg/rcomp/tmp/43l0o1393364019.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qq.plot(resid(lmxdf), main='QQplot of Residuals of Fit') Warning message: 'qq.plot' is deprecated. Use 'qqPlot' instead. See help("Deprecated") and help("car-deprecated"). > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5oh7z1393364019.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(xdf$X, resid(lmxdf), main='Scatterplot of Residuals of Model Fit') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/6oo9n1393364019.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot.lm(lmxdf, which=4) > dev.off() null device 1 > > try(system("convert tmp/3yypx1393364019.ps tmp/3yypx1393364019.png",intern=TRUE)) character(0) > try(system("convert tmp/43l0o1393364019.ps tmp/43l0o1393364019.png",intern=TRUE)) character(0) > try(system("convert tmp/5oh7z1393364019.ps tmp/5oh7z1393364019.png",intern=TRUE)) character(0) > try(system("convert tmp/6oo9n1393364019.ps tmp/6oo9n1393364019.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.206 0.679 3.892