Measuring continuous change or growth in individual students' academic abilities over time currently uses several statistical models or transformations to move from data representing a student's correct or incorrect responses on individual test items to inferences about the form and quantity of...

This article explores Bayesian joint models of event times and longitudinal measures with an attempt to overcome departures from normality of the longitudinal response, measurement errors, and shortages of confidence in specifying a parametric time-to-event model. We allow the longitudinal...

Mixed hidden Markov models have been recently defined in the literature as an extension of hidden Markov models for dealing with population studies. The notion of mixed hidden Markov models is particularly relevant for modeling longitudinal data collected during clinical trials, especially when...