dset<-structure(list(V1 = c(100L, 90L, 80L, 70L, 60L, 50L, 40L, 30L, 20L, 10L), V2 = c(0, 0.003841788, -0.001492275, -0.000219173, -0.002724556, 0.00336318, -0.012693059, -0.010003541, -0.006839342, -0.020346107), V3 = c(0, 0.001393081, 0.002897879, 0.001972387, 0.000464792, 0.002782286, 0.002782286, -0.000697999, 0.004973973, 0.011605194), V4 = c(0, -0.004692156, -0.005776311, -0.027694902, -0.012266019, -0.029263698, -0.052509217, -0.083641089, -0.110293602, -0.011652035), V5 = c(0, -0.002138334, -0.003541426, -0.002633095, -0.003045769, 0.002782552, -0.000903565, 0.002864157, 0.018921095, 0.013759611)), .Names = c("V1", "V2", "V3", "V4", "V5"), class = "data.frame", row.names = c(NA, -10L)) attach(dset) ## plot the data plot(V1,V2, ylim=c(-0.15,0.15), xlab='Number of imputations',ylab='Relative deviance (ab)') lines(V1,V2) points(V1,V3) lines(V1,V3, lty=2) legend('topright', c('Estimate','S.E.'), lty=c(1,2), bty='n') ## for 40% plot(V1,V4, ylim=c(-0.15,0.15), xlab='Number of imputations',ylab='Relative deviance (ab)') lines(V1,V4) points(V1,V5) lines(V1,V5, lty=2) legend('topright', c('Estimate','S.E.'), lty=c(1,2), bty='n')