Small dataset causing SE=0 and CI=beta estimate?

[roobydooby]

Hello,
I am trying to build a set of models to investigate factors affecting nest survival of two species for which I have little data (8 nests for one, and 16 for the other). I am interested in 4 variables: nest height, nest age, linear time trend and quadratic time trend. Beta estimates and associated variance is fine when building models of each variable independently. But when I build a kitchen sink model, SE for the beta estimates of intercept, linear and quadratic time trends are 0 and the upper and lower CI are identical to the beta estimate. Although I am certainly capable of doing things incorrectly, I don't believe I have set up the inp file or design matrix incorrectly. I have successfully run these same models, and more complex ones, with larger datasets more times than I can count. I am wondering if anyone can confirm that this is likely happening due to small sample sizes? Should I just kick out global model, or is there something I am doing wrong... besides being ambitious with my data? Thank you in advance for your time.

[roobydooby]

So, as far as I can tell, I was correct that my issue is too few data. I found in the Mark help files suggestions to change the optimization method (the “Error number 2 from VA09AD optimization routine” popped up when later running my smaller, 8 nest dataset). Although it suggests to use this method with caution, I cannot see that I have a better alternative. I now have SE for beta estimates.