0

I am running a non-linear mixed model in nlme, and I am having trouble calculating the standard errors of the three parameters. We have our final model here:

shortG.nlme9 <- update(shortG.nlme6,
                   fixed = Asym + xmid + scal ~ Treatment * Breed + Environment,
                   start = c(shortFix6[1:16], rep(0,2),
                             shortFix6[17:32], rep(0,2),
                             shortFix6[33:48], rep(0,2)),
                   control = nlmeControl(pnlsTol = 0.02, msVerbose = TRUE))

And when we plug it in with the summary statement, we can get the standard errors of each of the treatments, breeds, treatment*breed interactions, and environments. However, we are looking at making growth curves for specific combinations (treatment1/breed1, treatment2/breed1, treatment3/breed1, etc), so we need to combine effects of treatment, breed, and the environments for the parameter values, and logically combine their standard errors to get the SE of the full parameter. To do this, is there either a way to get R to come up with the full SE on its own, or is there an easy way to have R give us a covariate matrix so we can calculate the values by hand? When we look at the basic statistics by simply plugging in the summary(shortG.nlme9) statement, we are automatically given a correlation matrix, so is there something we could write in for a covariate matrix instead?

Michael
  • 75
  • 1
  • 9
  • 1
    Does `vcov` on the resulting object work? Can't test at the moment and don't use nlme often so I can't be sure it does but it sounds like it should work... – Dason Sep 05 '14 at 22:29
  • Dason, It looks like it does work, however, the resulting output is absolutely massive, and only a small portion of it is actually visible (using R Studio). I was wondering if you knew of a way to send the output to something like a word document. – Michael Sep 11 '14 at 15:59

0 Answers0