Home > Events > 2013 Seminars & Colloquia > CHENG YONG TANG - University of Colorado Denver

CHENG YONG TANG - University of Colorado Denver

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” A Joint Modeling Approach for Longitudinal Studies”
When
05 December 2013 from 4:00 PM to 5:00 PM
Where
201 Thomas Bldg.
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In longitudinal studies, it is of fundamental importance to understand the dynamics in the mean function, variance function, and correlations of the repeated or clustered measurements. For modeling the covariance structure, Cholesky type decomposition based approaches are demonstrated effective. However, parsimonious approaches for directly revealing the correlation structures among longitudinal measurements remain less explored and existing approaches may encounter difficulty when interpreting the covariation structure of the longitudinal measurements. We propose in this paper a novel joint mean-variance-correlation modeling approach for longitudinal studies. By applying hyperspherical coordinates, we obtain an unconstrained interpretable parametrization of the correlation matrix.  We then propose a regression approach to model the correlation matrix of the longitudinal measurements by exploiting the unconstrained parametrization. The proposed modeling framework is parsimonious, interpretable, flexible, and it automatically guarantees the resulting correlation matrix to be non-negative definite. Extensive data examples and simulations support the effectiveness of the proposed approach. This is a joint work with Weiping Zhang and Chenlei Leng.

Some key words: Correlation matrix; Hyperspherical coordinates; Joint modeling; Modified Cholesky decomposition; Longitudinal data analysis.