A first-order transition model is used to analyze repeated measurement or longitudinal ordinal response data to compare several treatments for which measurements for each subject occur both at baseline and at follow-up. The likelihood function is partitioned to make possible the use of existing software for estimating model parameters. Data from a clinical trial illustrate the application of the transition model. Nagelkerke's pseudo-R2 is used for the goodness of fit of the model.
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