We investigate the performance of jackknife estimators based on maximum likelihood estimators of log-liner models for Poisson observations. We find that though for very simple models jackknifing may improve both bias and variance, in general there is no such strong optimum. We suggest new more accurate estimates for the variances of the estimators.