The Analysis of Dark Adaptation Data
Description
The recovery of visual sensitivity in a dark environment is known as dark
adaptation. In a clinical or research setting the recovery is typically
measured after a dazzling flash of light and can be described by the Mahroo,
Lamb and Pugh (MLP) model of dark adaptation. The functions in this package
take dark adaptation data and use nonlinear regression to find the parameters
of the model that 'best' describe the data. They do this by firstly,
generating rapid initial objective estimates of data adaptation parameters,
then a multi-start algorithm is used to reduce the possibility of a local
minimum. There is also a bootstrap method to calculate parameter confidence
intervals. The functions rely upon a 'dark' list or object. This object is
created as the first step in the workflow and parts of the object are
updated as it is processed.