[R] problem with intervals in mixed model

From: Bill Shipley <bill.shipley_at_usherbrooke.ca>
Date: Wed 11 May 2005 - 04:46:32 EST

Hello. I am analysing data from a mixed model perspective using the lme() function. The fixed effects model is a quadratic (Y~X+X2) where X2 is the square of X and the data have a 3-level structure. I fitted a series of three models with the same fixed effects but differing in the random effects (only intercept, intercept + X, intercept +X +X2). The anova shows that all three parameters vary significantly (p<0.001) across groups. I have therefore chosen the third model, in which all three parameters vary.

When I attempted to obtain the confidence intervals for the correlations between the random components, using:  


I get the following error message:  

Problem in intervals.lme(fit3, which = "var..: Cannot get confi

dence intervals on var-cov components: Non-positive definite ap

proximate variance-covariance    

I assume that this arises because the correlation between two of the parameters at the 2nd lowest level is -0.998. Can anyone tell me how to deal with this problem? Specifically,

  1. how should I interpret such a strong correlation?
  2. how can I obtain confidence intervals for these correlations between the random components?

Any help is appreciated.  

Bill Shipley  

        [[alternative HTML version deleted]]

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 Received on Wed May 11 04:52:33 2005

This archive was generated by hypermail 2.1.8 : Fri 03 Mar 2006 - 03:31:41 EST