  The statistical analysis of enzyme kinetic reactions usually involves models
of the response functions which are well defined on the basis of
Michaelis-Menten type equations. The error structure however is often without
good reason assumed as additive Gaussian noise. This simple assumption may lead
to undesired properties of the analysis, particularly when simulations are
involved and consequently negative simulated reaction rates may occur. In this
study we investigate the effect of assuming multiplicative lognormal errors
instead. While there is typically little impact on the estimates, the
experimental designs and their efficiencies are decisively affected,
particularly when it comes to model discrimination problems.
