Qing Lu, Ph.D

Liu R, Li C, Lu Q. Neural-network transformation models for counting processes. Stat. Anal. Data Min.: ASA Data Sci. J.15 (2022), 322– 338.

Shen X, Jiang C, Sakhanenkob L, Lu Q. A goodness-of-fit test based on neural network sieve estimators. Statistics & Probability Letters. 2021; 174: 109100.

Wen Y and Lu Q. An optimal kernel-based multivariate U-statistic to test for associations with multiple phenotypes. Biostatistics. 2020 Oct 26; kxaa049.

Jadhav S, Koul H, Lu Q. Dependent Generalized Functional Linear Models. Biometrika 2017;104(4):987-994.

Wen Y, Burt A, Lu Q. Risk Prediction Modeling on Family-Based Sequencing Data Using a Random Field Method. Genetics. 2017; 207(1):63-73.

Wei C and Lu Q. A generalized association test based on U statistics. Bioinformatics. 2017; 33(13):1963-1971.

Wei C, Elston RC, and Lu Q. A weighted U statistic for association analyses considering genetic heterogeneity. Statistics in Medicine. 2016; 35(16):2802-14.

He Z, Zhang M, Zhan X and Lu Q. Modeling and Testing for Joint Association Using a Genetic Random Field Model. Biometrics. 2014;70(3):471-9.

Lu Q, Obuchowski N, Won S, Zhu X, Elston RC. Using the robust optimal receiver operating characteristic curve for predictive genetic tests. Biometrics. 2010; 66(2):586-93.

Lu Q, Elston RC. Using the optimal receiver operating characteristic (ROC) curve to design a predictive genetic test exemplified with Type 2 Diabetes. Am J Hum Genet. 2008; 82(3):641-51.