Current Research Interests
Pooled Biomonitoring
Group Testing
Order-restricted Inference
Nonparametric and Semiparametric Regression
Shrinkage Methods
Quantile Regression
Publications
Acknowledgment: research is supported by NIH (R03 AI135614, R21 AG070659) and USC ASPIRE I.
*Advisee
Pooled Biomonitoring
Mou, X. and Wang, D. (2024). Additive partially linear model for pooled biomonitoring data. Computational Statistics and Data Analysis 190, 107862 [Rcode: APLMforPool]
Liu, Y., Wang, D., Li, L., and Li, D. (2023). Assessing disparities in Americans' exposure to PCBs and PBDEs based on NHANES pooled biomonitoring data. Journal of American Statistical Association 118, 1528-1550. [pdf, supp]
Wang, D., Mou, X.*, and Liu, Y. (2022). Varying coefficient regression analysis for pooled biomonitoring data. Biometrics 78, 1328-1341. [R code: VCMforPB]
Wang, D., Mou, X.*, Li, X., and Huang, X. (2020). Local polynomial regression for pooled response data. Journal of Nonparametric Statistics 32, 814-837. [R code: LPRforPool]
Lin, J.* and Wang, D. (2018). Single-index regression analysis of pooled biomarker assessments. Journal of Nonparametric Statistics 30, 813-833. [R code: SimPool]
Group Testing
Li, Y.*, Wang, D., and Tebbs, J. (2024+). Regularized Bayesian varying coefficient regression for group testing data. Biostatistics, submitted.
Hou, P.*, Tebbs, J. , Wang, D., McMahan, C., and Bilder, C. (2020). Array testing with multiplex assays. Biostatistics 21, 417-431. [R code: Multiplex][R Shiny App: MultiGTSiM]
Lin, J.*, Wang, D., and Zheng, Q. (2019). Regression analysis and variable selection for two-stage multiple-infection group testing data. Statistics in Medicine 38, 4519-4533.
Gregory, K., Wang, D., and McMahan, C. (2018). Adaptive elastic net for group testing data. Biometrics 75, 13-23. [R code: aenetget]
Wang, D., McMahan, C., Tebbs, J., and Bilder, C. (2018). Group testing case identification with biomarker information. Computational Statistics and Data Analysis 122, 156-166. [R code: GTwBiomarker]
Wang, D., McMahan, C., and Gallagher, C. (2015). A general parametric regression framework for group testing data with dilution effects. Statistics in Medicine 34, 3606-3621. [R code: GTDilution]
Wang, D., McMahan, C., Gallagher, C., and Kulasekera, K. (2014). Semiparametric group testing regression models. Biometrika 101, 587-598.
Wang, D., Zhou, H., and Kulasekera, K. (2013). A semi-local likelihood regression estimator of the proportion based on group testing data. Journal of Nonparametric Statistics 25, 209-221.
Order-restricted Inference
Zhuang, W., Yang, W., and Wang, D. (2024+). A consistent semi-parametric test for bivariate stochastic dominance. Statistica Sinica, under review.
Tang, C. and Wang, D. (2023+). Multiple ordinal dominance curves and uniform stochastic ordering. Statistica Sinica, in press. [R code: MSUSO]
Wang, D. and Tang, C.* (2021). Testing against uniform stochastic ordering with paired observations. Bernoulli 27, 2556-2563. [R package: TestUSO]
Tang, C.*, Wang, D., El Barmi, H., and Tebbs, J. (2021). Testing for positive quadrant dependence. American Statistician 75, 23-30. [R code: PQD]
Wang, D., Tang, C.*, and Tebbs, J. (2020). More powerful goodness-of-fit tests for uniform stochastic ordering. Computational Statistics and Data Analysis 144, 106898. [R code: ImprovedGOFforUSO]
Tang, C.*, Wang, D., and Tebbs, J. (2017). Nonparametric goodness-of-fit tests for uniform stochastic ordering. Annals of Statistics 48, 2565-2589. [R package: TestUSO]
Others
Cao, X.* and Gregory, K., and Wang, D. (2022). Inference for sparse linear regression based on the leave-one-covariate-out solution path. Communications in Statistics–Theory and Methods 52, 6640-6657.
Wang, D., Jiang, C., and Park, C. (2019). Reliability analysis of load-sharing systems with memory. Lifetime Data Analysis 25, 341-360. [R code: LSMwMemory]
Russell, B., Wang, D., and McMahan, C. (2017). Spatially modeling the effects of meteorological drivers of PM2.5 in the eastern United States via a local linear penalized quantile regression estimator. Environmetrics 28, 1-16.
Wang, D. and Kulasekera, K. (2012). Parametric component detection and variable selection in varying-coefficient partially linear models. Journal of Multivariate Analysis 112, 117-129.