This command
cdmoutcome<- glm(log(value)~factor(year) > +log(gdppcpppconst)+log(gdppcpppconstAII) > +log(co2eemisspc)+log(co2eemisspcAII) > +log(dist) > +fdiboth > +odapartnertohost > +corrupt > +log(infraindex) > +litrate > +africa > +imr > , data=cdmdata2, subset=zero==1, gaussian(link = > "identity")) results in this table Coefficients: (1 not defined because of singularities) > Estimate Std. Error t value Pr(>|t|) > (Intercept) 1.216e+01 5.771e+01 0.211 0.8332 > factor(year)2006 -1.403e+00 5.777e-01 -2.429 0.0157 * > factor(year)2007 -2.799e-01 7.901e-01 -0.354 0.7234 > log(gdppcpppconst) 2.762e-01 5.517e+00 0.050 0.9601 > log(gdppcpppconstAII) -1.344e-01 9.025e-01 -0.149 0.8817 > log(co2eemisspc) 5.655e+00 2.903e+00 1.948 0.0523 . > log(co2eemisspcAII) -1.411e-01 4.245e-01 -0.332 0.7399 > log(dist) -2.938e-01 4.023e-01 -0.730 0.4658 > fdiboth 1.326e-04 1.133e-04 1.171 0.2425 > odapartnertohost 2.319e-03 1.437e-03 1.613 0.1078 > corrupt 1.875e+00 3.313e+00 0.566 0.5718 > log(infraindex) 4.783e+00 1.091e+01 0.438 0.6615 > litrate0.47 -2.485e+01 3.190e+01 -0.779 0.4365 > litrate0.499 -1.657e+01 2.591e+01 -0.639 0.5230 > litrate0.523 -2.440e+01 3.427e+01 -0.712 0.4769 > litrate0.528 -9.184e+00 1.379e+01 -0.666 0.5060 > litrate0.595 -2.309e+01 2.776e+01 -0.832 0.4062 > litrate0.66 -1.451e+01 2.734e+01 -0.531 0.5961 > litrate0.675 -1.707e+01 2.813e+01 -0.607 0.5444 > litrate0.68 -6.346e+00 1.063e+01 -0.597 0.5509 > litrate0.699 2.717e+00 3.541e+00 0.768 0.4434 > litrate0.706 -1.960e+01 2.933e+01 -0.668 0.5046 > litrate0.714 -2.586e+01 4.002e+01 -0.646 0.5186 > litrate0.736 5.641e+00 1.561e+01 0.361 0.7181 > litrate0.743 -2.692e+01 4.253e+01 -0.633 0.5273 > litrate0.762 -2.208e+01 3.100e+01 -0.712 0.4767 > litrate0.802 -2.325e+01 3.766e+01 -0.617 0.5375 > litrate0.847 -2.620e+01 3.948e+01 -0.664 0.5075 > litrate0.86 -3.576e+01 4.950e+01 -0.722 0.4707 > litrate0.864 -4.482e+01 6.274e+01 -0.714 0.4755 > litrate0.872 -1.946e+01 2.715e+01 -0.717 0.4739 > litrate0.877 -2.710e+01 3.702e+01 -0.732 0.4646 > litrate0.879 -3.460e+01 5.147e+01 -0.672 0.5020 > litrate0.886 -3.276e+01 4.860e+01 -0.674 0.5008 > litrate0.889 -4.120e+01 5.755e+01 -0.716 0.4746 > litrate0.904 -2.282e+01 2.985e+01 -0.764 0.4453 > litrate0.91 -3.478e+01 5.037e+01 -0.691 0.4904 > litrate0.923 -1.762e+01 2.551e+01 -0.691 0.4902 > litrate0.925 -2.445e+01 3.611e+01 -0.677 0.4990 > litrate0.926 -2.995e+01 4.565e+01 -0.656 0.5123 > litrate0.928 -2.839e+01 3.933e+01 -0.722 0.4710 > litrate0.937 -2.571e+01 3.795e+01 -0.677 0.4986 > litrate0.94 -2.109e+01 3.051e+01 -0.691 0.4900 > litrate0.959 -2.078e+01 2.895e+01 -0.718 0.4735 > litrate0.96 -3.403e+01 4.798e+01 -0.709 0.4787 > litrate0.962 -4.084e+01 5.755e+01 -0.710 0.4785 > litrate0.971 -3.743e+01 5.247e+01 -0.713 0.4761 > litrate0.98 -3.709e+01 5.170e+01 -0.717 0.4737 > litrate0.986 -2.663e+01 4.437e+01 -0.600 0.5488 > litrate0.991 -3.045e+01 4.166e+01 -0.731 0.4654 > litrate1 -2.732e+01 4.459e+01 -0.613 0.5405 > africa NA NA NA NA > imr 2.160e+00 9.357e-01 2.309 0.0216 * although it should result in something similar to this: Coefficients: (1 not defined because of singularities) > Estimate Std. Error t value Pr(>|t|) > (Intercept) 1.216e+01 5.771e+01 0.211 0.8332 > factor(year)2006 -1.403e+00 5.777e-01 -2.429 0.0157 * > factor(year)2007 -2.799e-01 7.901e-01 -0.354 0.7234 > log(gdppcpppconst) 2.762e-01 5.517e+00 0.050 0.9601 > log(gdppcpppconstAII) -1.344e-01 9.025e-01 -0.149 0.8817 > log(co2eemisspc) 5.655e+00 2.903e+00 1.948 0.0523 . > log(co2eemisspcAII) -1.411e-01 4.245e-01 -0.332 0.7399 > log(dist) -2.938e-01 4.023e-01 -0.730 0.4658 > fdiboth 1.326e-04 1.133e-04 1.171 0.2425 > odapartnertohost 2.319e-03 1.437e-03 1.613 0.1078 > corrupt 1.875e+00 3.313e+00 0.566 0.5718 > log(infraindex) 4.783e+00 1.091e+01 0.438 0.6615 > litrate -2.485e+01 3.190e+01 -0.779 0.4365 > africa -2.732e+01 4.459e+01 -0.613 0.5405 > imr 2.160e+00 9.357e-01 2.309 0.0216 * In fact, if I don't use the litrate variable, the regression runs just fine. If I use the variable in a different regression, it also works fine. I just can't find the point where it turns ugly. I tested the litrate-variable for everything I know to test for: The structure is numerical and it does not contain any missings. It has the same length as every other variable in the set and is a continuous variable with values between 0 and 1. Does anyone have an idea? -- View this message in context: http://r.789695.n4.nabble.com/Regression-Error-Otherwise-good-variable-causes-singularity-Why-tp2322780p2322780.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.
