Evaluation of distribution-free confidence limits for enzyme kinetic parameters.

Monte Carlo experiments have been used to test the robustness of distribution-free confidence limits for the parameters of the MichaelisMenten equation (Porter & Trager, 1977). When used in conjunction with the modified form of the direct linear plot (Cornish-Bowden & Eisenthal, 1978), they prove to be more robust than least-squares confidence limits. In circumstances where the least-squares assumptions are correct, the distribution-free confidence limits define the parameters somewhat less precisely than the corresponding least-squares confidence limits, but this effect is negligible unless there are eight or fewer observations.