A Latent Model Approach to Study Postural Instability for Parkinson´s Disease

Postural instability is an important measure of Parkinson´s disease conditions. Because of the fluctuation of clinical symptoms and large inter-rater and intra-rater variation, traditional method of analyzing postural instability using its onset time measure can result in controversial conclusion of treatment benefit. We propose a Brownian motion based latent structure model to study treatment´s effect on postural instability The new method not only incorporates patient´s multiple onset times, but also the special covariate structure of postural instability process. The proposed model does not require even-spaced visiting schedules, and the correlation of the binary process is naturally built through the underlying latent Brownian motion process. Theoretical and computational properties of the proposed model are examined. A dataset from a double-blinded multicenter Parkinson´s disease clinical trial is used to demonstrate the methodology.