Research Interests
Before joining UNC in 2001, I had been on the faculty at the University of Washington's Department of Biostatistics for 10 years. While at the University of Washington, I had a joint appointment with the Fred Hutchinson Cancer Research Center. I worked closely with the clinicians at the Hutchinson Cancer Center. The collaborations led to papers #26 and #39 in my curriculum vitae.

Most of my work, both at the University of Washington and University of North Carolina, is concerned with the development of statistical methods for the designs and analysis of clinical and epidemiological cancer studies. Currently, I have two R01 grants.

The first one is "Statistical Methods in Current Cancer Research," funded by the National Cancer Institute. The broad, long-term objectives of this grant are the developments of simple and useful statistical methods for the design and analysis of clinical and epidemiologic cancer studies with incomplete observations. The specific aims include: (1) investigation of semi-parametric regression methods for assessing the effects of covariates (e.g., cancer therapy and patient characteristics) on medical cost and quality-adjusted lifetime based on incomplete follow-up data, (2) construction of non- and semi-parametric methods for the joint analysis of incomplete repeated measures (e.g., serial quality-of-life measures)


and censored failure times (e.g., times to cancer recurrence/death) from longitudinal cancer studies, and (3) exploration of efficient methods of design and analysis for two-phase survival studies (e.g., case-cohort studies, sample surveys and covariate measurement error problems). The proposed statistical models and inference procedures are built from, but extend significantly, the current knowledge about the analysis of censored failure time data and incomplete repeated measures. These models are highly flexible and versatile in that they do not require specifying the distributional form of any random variable or the dependence structure between any two related outcome measures. The usefulness of the proposed methods is illustrated with real cancer studies.

My second RO1 grant is "Semiparametric Regression Analysis of Censored Data," which has been funded by the National Institute of General Medical Sciences since 1992. The broad, long-term objectives of this grant are the developments of non- and semi-parametric statistical methods for analyzing censored data commonly encountered in cancer research. The specific aims include: (1) generalization of the Cox regression model to allow non-proportional hazards struCtures; (2) construction of simple and reliable inference procedures for the semi parametric accelerated failure time model; (3) exploration of efficient estimation procedures for the marginal modellings of multivariate failure time data; (4) derivation of non parametric tests and semiparametric regression methods for growth curves under informative heterogeneous censoring. These topics are motivated by and directly relevant to cancer applications. The statistical models under investigation are highly flexible and versatile, imposing no parametric form on the distribution of any random variable. The proposed inference procedures are relatively simple and efficient. Applications to real cancer studies are provided.

In addition to the specific aims listed in my two RO1 grants, I am currently developing statistical methods for genetic cancer studies. These methods include: (1) linkage analysis for experimental crosses with censored quantitative traits; (2) linkage analysis in humans with longitudinal quantitative traits; (3) association mappings in structured populations. These topics will be part of the competing renewal application of my NCI grant.

Recent Accomplishments and Honors
Mortimer Spiegelman Award, American Public Health Association, 1999
Fellow, Institute of Mathematical Statistics, 1999
Fellow, American Statistical Association, 2000
JASA Theory and Methods Discussion Paper, 2000
Myrto Lefkopoulou Distinguished Lecturer, Harvard School of Public Health, 2002

Training
East China Nonnal University, Shanghai, PRC, B.S., 1983, Geography
University of Michigan, Ann Arbor, MI, M.S., 1986, Biostatistics
University of Michigan, Ann Arbor, MI, Ph.D., 1989, Biostatistics

Publications
Wei LJ, Lin DY, Weissfeld L: Regression analysis of multivariate incomplete failure time data by modeling marginal distributions.
JASA 84:1065-1073,1989.
Lin DY, Wei LJ: The robust inference for the Cox proportional hazards model. JASA 84:1074-1078, 1989.
Wei LJ, Ying Z, Lin DY: Linear regression analysis of censored survival data based on rank tests. Biometrika 77:845-851, 1990.
Lin DY: Nonparametric sequential testing in clinical trials with incomplete multivariate observations. Biometrika 78:123-131, 1991.
Lin DY: Goodness-of-fit analysis for the Cox regression model based on a class of parameter estimators. JASA 86:725-728, 1991.
Lin DY, Wei LJ, DeMets DL: Exact statistical inference for group sequential trials. Biometrics 47:1399-1408,1991.
Lin DY: Sequential log rank tests adjusting for covariates with the accelerated life model. Biometrika 79:523-529, 1992.
Lin DY, Liu PY: Nonparametric sequential tests against ordered alternatives in multiple-anned clinical trials. Biometrika 79:420-425, 1992.
Lin DY, Geyer CJ: Computational methods for semiparametric linear regression with censored data. J Comput Graph Stat 1:77-90, 1992.
Lin DY, Fischl MJ, Schoenfeld DA: Evaluating the role of CD4-lymphocyte changes as surrogate endpoints in human immunodeficiency virus clinical trials. Stat Med 12:835-42, 1993.

E-mail: lin@bios.unc.edu
Telephone: 919-843-5134
FAX: 919-966-3804
Address: 3101E McGavren-Greenberg Chapel Hill, NC

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