Another way to estimate the variability of model parameters is to use resampling statistics such as the Jackknife or Bootstrap approach. Basically a Jackknife estimate of the parameter error is obtained by removing one point from your data set,fitting your model to the remaining data, record the estimated parameters, replacing the data point, remove another and refit the model and recording the new estimates--repeat until all data points are removed and replaced. The set of estimated parameter values can be to create the cumulative frequency distribution and thus the variability of the parameter estimates. see http://en.wikipedia.org/wiki/Resampling_(statistics) Bruce Peterson, Ph.D. Terastat, Inc Information Access Systems Voice (425) 466 7344