Assessment of the influence is an important part of regression diagnostics. The measure of influence in linear regression has been extended to nonlinear regression. The connections between measures of influence and leverage are explored. We suggest a modification of the influence measure for assessing the influential observations on the parameter estimates in a nonlinear regression model.