  We present a method to compare spatial interaction models against data based
on well known statistical measures that are appropriate for such models and
data. We illustrate our approach using a widely used example: commuting data,
specifically from the US Census 2000. We find that the radiation model performs
significantly worse than an appropriately chosen simple gravity model. Various
conclusions are made regarding the development and use of spatial interaction
models, including: that spatial interaction models fit badly to data in an
absolute sense, that therefore the risk of over-fitting is small and adding
additional fitted parameters improves the predictive power of models, and that
appropriate choices of input data can improve model fit.
