 The approach of estimating higher order distributional information on the basis of subdividing the available sample is similar to the modern statistical procedure of bootstrapping, although there re-sampling techniques are used. Reichenbach argues that his procedure ensures more efficient convergence than does naïve application of the straight rule alone. Faster convergence of the first level estimate—the data-level—is somehow supposed to result from simultaneous convergence at all the different levels in this hierarchy of appraised posits—Reichenbach refers to this as the method of cross-induction. But Creary (1969, Ch. 5) points out that there is no reading of such a conclusion about efficient convergence that follows from the premises Reichenbach assumes. 