Seminar Announcement**

* *

*Nonparametric estimation of conditional distributions and rank-tracking
probabilities with time-varying transformation models in longitudinal

*Colin O. Wu *

*Office of Biostatistics Research**

*National Heart, Lung and Blood Institute *

*National Institutes of Health*


*Engr 4201 (Computer science conference room)  *

*4400 University Drive, Fairfax, VA 22030***

*Time: 11:00 A.M. - 12:00 P.M.***

*Date: Friday, Mar 22, 2013 ***

* *


An important objective of longitudinal analysis is to estimate the
conditional distributions of an outcome variable through a regression
model. The approaches based on modeling the conditional means are not
appropriate for this task when the conditional distributions are skewed or
cannot be approximated by a normal distribution through a known
transformation. We study a class of time-varying transformation models and
a two-step smoothing method for the estimation of the conditional
distribution functions. Based our models, we propose a rank-tracking
probability and a rank-tracking probability ratio to measure the strength
of tracking ability of an outcome variable at two different time points.
Our models and estimation method can be applied to a wide range of
scientific objectives that cannot be evaluated by the conditional mean
based models. We derive the asymptotic properties for the two-step local
polynomial estimators of the conditional distribution functions. Finite
sample properties of our procedures are investigated through a simulation
study. Application of our models and estimation method is demonstrated
through a large epidemiological study of childhood growth and blood

*This is the joint work with Xin Tian (OBR/NHLBI)

Yunpeng Zhao, PhD

Assistant Professor
Department of Statistics
Volgenau School of Engineering <[log in to unmask]>
George Mason University
Engineering Building, Room 1719, MS 4A7
4400 University Drive
Fairfax, VA 22030-4444

Phone: 703-993-1674
Email: [log in to unmask]