Dear R users, i'm using a custom function to fit ancova models to a dataset. The data are divided into 12 groups, with one dependent variable and one covariate. When plotting the data, i'd like to add separate regression lines for each group (so, 12 lines, each with their respective individual slopes). My 'model1' uses the group*covariate interaction term, and so the coefficients to plot these lines should be contained within the 'model1' object (there are 25 coefficients and it looks like I need the last 12). The problem is I can't figure out how to extract the relevant coefficients from 'model1' and add them using abline. I imagine there's some way of using the relevant slopes
abline(model1$coef[14:25]) together with the intercept, but I can't quite get it right. Can anyone offer a suggestion as to how to go about this? Ideally, What i'd like is to plot each regression line in the same color as the group to which it belongs. I've provided an example with dummy data below best, Steve # =========================================================== # hypothetical data species <- c(1,1,1,2,2,2,3,3,3,3,4,4,4,5,5,5,5,6,6,6,7,7,7,8,8,8,8,9,9,9,9,9,10,10,10,11,11,11,11,12,12,12,12,12) beak.lgth <- c(2.3,4.2,2.7,3.4,4.2,4.8,1.9,2.2,1.7,2.5,15,16.5,14.7,9.6,8.5,9.1,9.4,17.7,15.6,14,6.8,8.5,9.4,10.5,10.9,11.2,11.5,19,17.2,18.9,19.5,19.9,12.6,12.1,12.9,14.1,12.5,15,14.8,4.3,5.7,2.4,3.5,2.9) mass <- c(45.9,47.1,47.6,17.2,17.9,17.7,44.9,44.8,45.3,44.9,39,39.7,41.2,84.8,79.2,78.3,82.8,102.8,107.2,104.1,51.7,45.5,50.6,27.5,26.6,27.5,26.9,25.4,23.7,21.7,22.2,23.8,46.9,51.5,49.4,33.4,33.1,33.2,34.7,39.3,41.7,40.5,42.7,41.8) dataset <- cbind(groups, beak.lgth, mass) # ANCOVA function anc <- function(variable, covariate, group){ # transform data lgVar <- log10(variable) lgCov <- log10(covariate) # separate regression lines for each group model1 <- lm(lgVar ~ lgCov + group + lgCov:group) model1.summ <- summary(model1) model1.anv <- anova(model1) # separate regression lines for each group, but with the same slope model2 <- lm(lgVar ~ lgCov + group) model2.summ <- summary(model2) model2.anv <- anova(model2) # same regression line for all groups model3 <- lm(lgVar ~ lgCov) model3.summ <- summary(model3) model3.anv <- anova(model3) compare <- anova(model1, model2, model3) # compare all models # plots par(mfcol=c(1,2)) boxplot(lgVar ~ group, col="darkgoldenrod1") # plot the variate and covariate by group plot(lgVar ~ lgCov, pch=as.numeric(group), col=as.numeric(group)) legend("topleft", inset=0, legend=as.character(unique(group)), col=as.numeric(unique(group)), pch=as.numeric(unique(group)), pt.cex=1.5) abline(model1) # Need separate regression lines here list(model_1_summary=model1.summ, model_1_ANOVA=model1.anv, model_2_summary=model2.summ, model_2_ANOVA=model2.anv, model_3_summary=model3.summ, model_3_ANOVA=model3.anv, model_comparison=compare) } # call function anc(beak.lgth, mass, species) # =========================================================== -- View this message in context: http://n4.nabble.com/Adding-regression-lines-to-each-factor-on-a-plot-when-using-ANCOVA-tp1748654p1748654.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.