American Statistical Association
New York City
Metropolitan Area Chapter

Mailman School of Public Health
Columbia University
Department of Biostatistics Colloquium



A DYNAMIC QUANTILE REGRESSION TRANSFORMATION MODEL
FOR LONGITUDINAL DATA

by

Yunming Mu
TAMU


Abstract

We propose a general multistate model. The model is developed for the analysis of repeated episodes of multiple states representing different health status. Different types of transition are described by flexible transition-specific nonparametric baseline intensities. Transitions among multiple states are modeled jointly using multivariate latent traits with factor loadings. A state-specific latent trait is used to capture individual tendency of the sojourn in the state that cannot be explained by covariates and to account for correlation among repeated sojourn in the same state within an individual. Correlation among sojourns across different states within an individual is accounted for by the correlation between the different latent traits. The factor loadings for a latent trait accommodate the dependence of competing transitions to different states from a same state. The method is illustrated by studying repeated transitions between independent and disabled states of activities of daily living (ADL) with death as an absorbing state in a longitudinal aging study.


Date: Thursday, March 8, 2007
Time: 4:00 to 5:00 P.M.
Location: Mailman School of Public Health
Department of Biostatistics
722 West 168th Street
Judith Jansen Conference Room (Room 425)
New York, New York

RESERVATIONS ARE NOT REQUIRED

Refreshments will be served at 3:30 P.M. in the
Biostatistics Conference Room (Room 627).


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