unable to make model Hessian positive definite - help!

Hello all,

My first time posting here, and really hoping that someone can help me out!
I have data from a repeated measures experiment in which the time points were not evenly spaced + some missing data from individual animals, so I am using proc mixed and attempting to find the appropriate covariance structure. I am doing this in two different models - one that includes 3 different time points (days 4, 6, and 7) and one that includes 5 different time points (days 8, 9, 10, 11 and 13).
I know that the unequal spacing in time isn't hugely "unequal" but in any case it isn't completely consistent, either...
Initially I tried sp(pow) and it gives me the message that the model converges but is not Hessian positive definite. Then I tried ante(1) and got the same message.
I am vaguely aware that this can occur if the model is over-fitted but as far as I can tell the model is pretty much bare bones right now (has the effect of health status, time, and their interaction, and the error term is animal nested in health status. My statistics consultant on campus said that the problem may be that I have relatively few time points and it is trying to estimate the appropriate parameters based on just a few time points and that I shouldn't necessarily be concerned with it not being Hessian positive definite.
When I ask for the covariance parameter estimates it gives me 0's for all of the "Rhos" but everything else is estimated.
I wonder if anyone can help me determine whether there are other options or whether I should just "turn a blind eye" to this problem and continue along in my analysis as if I wasn't getting this message.
I'm new to all of this so I have no idea what would definitively tell me if it's "ok" or not, and I am anxious to proceed with my analysis.

Thank you,