  We discuss a goodness-of-fit method which tests the compatibility between
statistically independent data sets. The method gives sensible results even in
cases where the chi^2-minima of the individual data sets are very low or when
several parameters are fitted to a large number of data points. In particular,
it avoids the problem that a possible disagreement between data sets becomes
diluted by data points which are insensitive to the crucial parameters. A
formal derivation of the probability distribution function for the proposed
test statistic is given, based on standard theorems of statistics. The
application of the method is illustrated on data from neutrino oscillation
experiments, and its complementarity to the standard goodness-of-fit is
discussed.
