  This article provides rigorous proofs that neither Efron's bootstrap nor
permutation techniques can be applied directly to the observations to construct
consistent resampling tests for transition probability matrices of finite-state
Markov processes. These methods modify the covariance functions of the limiting
distributions of the involved Aalen-Johansen processes, even in the case of
fully observable individuals. An example for the failure of these resampling
methods is given by cumulative incidence functions in competing risks set-ups.
