Hi Josh, Thanks for your response !
Actually, I already tried to plot it with a "classical" regression and I know the relation is linear: dA = 0.765 * dCOM - 0.089 p(slope) < 0.0001 p(intercept) = 0.0003 The fact is that I can not use these results as my variables dA and dCOM are correlated (as mentioned above, Eq.1). What I need to find out is which correction I should do on my data, and how, to be able to calculte the regression p-values correctly with Linear Mixed Models. I am interested in this because I know that my species decline at different rates when my community is declining. For example, with decreasing values of dCOM, dA reaches 0 before dB. Julie -- View this message in context: http://r.789695.n4.nabble.com/Calculating-plotting-a-linear-regression-between-two-correlated-variables-tp4319051p4320764.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.
