Dear list members, I am working with a multilevel growth curve, that in its simplest form goes like follows:
Yit = Ai + Bi t + eit (the error term is assumed to follow an AR(1) autorregressive process) One major topic in my research is the convergence in the values of Y over time. Thus, I am interested in the relationship between the random effects for the intercept and the slope, and I have a couple of questions about this: First, I have fitted the model using the nlme library in R, and the estimates for the random effects yield a correlation of -0.27. However, if I take values for random intercepts and slopes from the lme model, and run a correlation (or a regression) between them, I get a slightly positive relationship (R~ 0.02). How can this difference be explained? Second, I am also interested in the size of the relationship between intercept and slope. In other terms, in the rate of convergence. In order to analyze this, does it make any sense if use the values from my random-effects model and run an OLS regression using subject-specific intercepts as a covariate to explain subject-specific slopes? The results I mention above meake me suspicious about this, but I still do not know if it would be correct from a statistical standpoint. Thanks a lot, Antonio _________________________________________________________________ Moda para esta temporada. Ponte al día de todas las tendencias. ______________________________________________ R-help@stat.math.ethz.ch 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.