The value of r is found through cross-validation or a forward stage-wise strategy which stops when the model fit cannot be significantly improved.

The deviance information criterion is then used as measure of model fit.

Defining a metric to measure distances between observed and predicted data is a useful tool of assessing model fit.

These hypotheses examine model fit of the most common model:

The last line describes the omnibus F test for model fit.

This model fit used a permeability limitation (fclear) for muscle of 0.26.

But it is sort of a model fit.

As a rule of thumb, a large indicates a poor model fit.

This results in the likelihood ratio chi-square statistic being equal to 0, which is the best model fit.

A value of .06 or less is indicative of acceptable model fit.