Using nonlinear regression to estimate parameters of dark adaptation

Abstract

An objective technique for estimating the kinetics of dark adaptation is presented, with which one can evaluate models with multiple parameters, evaluate several models of dark adaptation simultaneously, and rapidly analyze large data sets. Another advantage is the ability to simultaneously estimate transition times and rates of sensitivity recovery. Finally, this nonlinear regression technique does not require that the distributional properties of the data be transformed, and thus, parameter estimates are in meaningful units and reflect the actual rate of recovery of sensitivity.