NOTE: Estimated G matrix is not positive definite. NOTE: Asymptotic variance matrix of covariance parameter estimates has been found to be singular and a generalized inverse was used. Covariance parameters with zero variance do not contribute to degrees of freedom computed by DDFM=KENWARDROGER. These notes are not show stoppers in any way.  The first says that there are more random effects in the model than can be fit with the data, while the second says, OK, now let's proceed with the analysis, and correct for those components whose estimates were zero. As far as the latter two analyses, I have to ask "Why"?  Why do subset analysis in the first case, when you already have accommodated any difference in fertility due to location AND made it applicable to locations beyond the ones fit in your first analysis.  Now if there is substantial heterogeneity in variance due to location, then that should be addressed, but probably not by a subset analysis. I like the approach of treating year as a random effect, and having only timing as a repeated effect with the sp(pow) error structure.  However, I would still include location as a random effect--it is a design factor, and dropping it to do subset analysis reduces power, while not including it ignores a design factor. Steve Denham Message was edited by: Steve Denham ... View more