Dec. 6 2005 2:00PM

Dec. 6 2005 3:30PM

Abstract: The increasing use of diary methods calls for the development of appropriate statistical methods. For the resulting panel data, latent markov models can be used to model both individual differences and temporal dynamics. The computational burden associated with these models can be overcome, at least partially, by exploiting the conditional independence relations implied by the model. This is done by associating a probabilistic model with a graph, and applying transformations to the graph. The usefulness of the approach is illustrated by estimating a latent markov model involving a large number of measurement occasions, and subsequently, a hierarchical extension of the latent markov model that allows for transitions at different levels. Furthermore, multinomial regression techniques are used to incorporate restrictions and to account for the effect of covariates. Throughout, models are illustrated with an experience sampling methodology study on the course of emotions aminy anorectic patients.

Pravidelný seminář Inteligentní systémy (Contact person: Tomáš Kroupa)