Finite Markov chains with absorbing states and mis-specified random effects: application to cognitive data
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Finite Markov chains with absorbing states are valuable tools for analyzing longitudinal data with categorical responses. However, defining the one-step transition probabilities in terms of fixed and random effects presents challenges due to the large number o... ...
