Precriterion stationarity in markovian learning models

Two forms of stationarity prior to criterion in absorbing Markov chains are examined. Both forms require that the probability of a particular response on a particular trial before absorption be independent of trial number. The stronger of these forms holds that this is true independent of starting state; the weaker, only for a specified set of starting probabilities. Simple, necessary and sufficient conditions for both forms are developed and applied to several examples.The author would like to thank Charles Lewis for his help in developing this article, and Peter Polson of the University of Colorado and an anonymous referee for several fruitful suggestions made in reviews of earlier versions.