Abstract: An expression for the second-order approximation to the kurtosis associated with the least squares estimate of an individual parameter in a nonlinear regression model is derived, and connections between this and various other measures of curvature are made. Furthermore a means of predicting the reliability of the commonly-used Wald confidence intervals for individual model parameters, based on measures of skewness and kurtosis, is developed. Numerous examples illustrating the theoretical results are provided.
Key words and phrases: Bias, confidence intervals, parameter-effects curvature, relative overlap, skewness.