In cases like this, I would strongly suggest you start by generating some synthetic data so that you know that your model mirrors the generating process and know the true values of each parameter. Then you can start with a small data set and see how things work out before tackling larger, more realistic (but still synthetic) data sets. Then you should have a bit more confidence when you finally turn to your real data.