Research Activities

Research Interest:

Longitudinal data analysis, survival analysis, Bayesian statistics, missing data, spatial analysis, risk prediction, model selection, high-dimensional data, and other areas related to public health, biomedical and environmental research.

Publications Invited for Revision or Under Review (* students under supervision;  + corresponding author):

1.  Wang, M.+,  Yang, Y.*, Chen, C.* and Liang, M.* (2024) Recent method development for joint modeling of recurrent events and a terminal event with risk prediction evaluation. Under review by the Springer Book on Big Data Analysis, Biostatistics and Bioinformatics.

2. Han, Y., Yang, Y.*,  Zhang, Z., Wang, M.+ and Liu, D.+ (2024) A Conditional Modeling Approach for Dynamic Risk Prediction of A Survival Outcome Using Longitudinal Biomarkers. Under review by the Springer Book on Big Data Analysis, Biostatistics and Bioinformatics. (Early version won Yongli the 2020 NCI Director’s Career Development Innovation Award)

3. Deng, D., Chinchilli, V.M., Zhang, L., Feng, H., Chen, C.+ and Wang, M.+ Enhanced time-to-event analysis with coarsened external data in the presence of discrte survival data. Biometrics, 2024. Invited for revision.

4. Liang, M., Yang, Y., Chinchilli, V.M., Chen, C. and Wang, M.+ (2024) Joint multivari- ate copula-frailty modeling of multiple-type recurrent events and the terminal event. Plan to submit to Biometrics. 

Methodology Publications (Note: The other collaborative publications can be referred to PUBLICATIONS):

1. Wang, M.+,  Li, Z.*, Lu, J.*, Zhang, L., Li. Y. and Zhang L.L. Spatial-Temporal Survival Analysis on Prostate Cancer in Pennsylvania Using Bayesian Accelerated Failure Time Models. BMC Medical Research Methodology, 2024. Accepted and to appear.

2. Deng, D., Chinchilli, V.M., Feng, H., Chen, C.+ and Wang, M.+ Robust integration of secondary data information into main outcome analysis in the presence of missing data. Statistical Methods in Medical Research, 2024. Accepted and to appear.

3. Wu, X.*, Chen, C.*, Li, Z.*, Zhang, L., Chinchilli, V.M. and Wang, M.+ A Three-Stage Approach to Identify Biomarker Signatures for Cancer Genetic Data with Survival Endpoints., Statistical Methods & Applications, 2024. Accepted and to appear. 

4. Chen, C.*, Chen, S., Long, Q., Das, S. and Wang, M.+ Multiple robust estimation and information integration for marginal causal effect under binary outcomes. American Statistician, 2023. Accepted and to appear.

5. Chen, C.*, Shen, B.* and Wang, M.+ ELCIC: An R package for model selection using the empirical-likelihood based information criterion. Communications for Statistical Applications and Methods, 2023. Accepted and to appear.

6. Liang, M.*, Li, Z.*, Li, L., Chinchilli, V.M., Zhang, L. and Wang, M.+ Dynamic risk prediction of recurrent events and death based upon Bayesian joint hierarchical copula models. Statistics in Medicine, 2023. In Press. 

7. Chen, C.*, Wang, M. and Shuo, C. An Efficient Data Integration Scheme to Synthesize Information from MultipleSecondary Outcomes to the Main Data Analysis. Biometrics, 2023. Accepted and to appear.

8.  Chen, C.*, Shen, B.*, Zhang, L., Yu, T.,  Wang, M.+ and Wu, R. A cartographic tool to predict Disease Risk-associated pseudo-Dynamic Networks from tissue-specific gene expression. Bio-Protocol, 2023; 13(0): e4583. 

9. Wang, M. and Long, Q. Addressing common misuses and pitfalls of P values in biomedical research. Cancer Research, 2022;82(15): 2674-2677.

10. Yang, Y., McDonald, A., Wang, X., Pan, Y. and Wang, M.+ Arsenic exposure and prostate cancer risk: a multilevel meta-analysis. Journal of Trace Elements in Medicine and Biology, 2022; 72: 126992. https://doi.org/10.1016/j.jtemb.2022.126992.

11. Chen, C.*, Yu, T., Shen, B.*, Wang, M. Synthesizing secondary data into survival analysis to improve estimation efficiency.  Biometrical Journal, 2022. https://doi.org/10.1002/bimj.202100326.

12. McDonald, A.+, Gernand, J., Geyer, N., Wu, H., Yang, Y. and Wang, M.+ Ambient Air Exposures to Arsenic and Cadmium and Overall and Prostate Cancer-Specific Survival among Prostate Cancer Cases in Pennsylvania, 2004-2014. Cancer, 2022; 128(9):1832-1839. doi: 10.1002/cncr.34128. (Co-corresponding author)

13. Chen, C.*, Shen, B.*, Ma, T., Wang, M.+ and Wu, R.+ A statistical framework for recovering pseudo-dynamic networks from static data.  Bioinformatics, 2022; 38(9): 2481-2487. 

14. Shen, B.*, Chen, C.*, Chinchilli, V.M., Ghahramani, N., Zhang, L. and Wang, M.+ Semiparametric marginal methods for longitudinal data adjust-ing for informative cluster size with non-ignorable zeros. Biometrical Journal, 2022; 64(5): 898-911.

15. Chen, C.*, Jiang, L., Shen, B.*, Wang, M., Griffin, C.H., Chinchilli, V. A and Wu, R.+ Computational Atlas of Tissue-specific Regulatory Networks. Frontiers in Systems Biology, 2021. https://doi.org/10.3389/fsysb.2021.764161. 

16. Shen, B.*, Chen, C.*, Liu, D., Datta, S., Ghahramani, N., Chinchilli, V.M. and Wang, M.+ A joint modeling of longitudinal data with informative cluster size adjusted for zero-inflation and a dependent terminal event. Statistics in Medicine, 2021; 40(21):4582-4596.

17. Chen, C.*, Wang, M.+,  Wu, R. and Li, R. Robust Consistent Information Criterion for Model Selection. Statistica Sinica, 2020;32: 1205-1223. (Early version won  Chixiang the 2019 ASA Nonparametric Section Student Paper Award).

18. Chen, C.*,  Shen, B., Liu, A.,  Wu, R. and Wang, M.+ A Multiple Robust Propensity Score Method for Longitudinal Analysis with Intermittent Missing Data.  Biometrics, 2020; 77(2):519-532.

19. Wang, M., Wasserman, E., Geyer, N., Carroll, R., Zhao, S., Hohl, R., Lengerich, E. and McDonald, A.  Spatial patterns in prostate cancer-specific mortality in Pennsylvania and its catchment area using Pennsylvania cancer registry data, 2004-2014. BMC Cancer, 2020;20(1): 394.

20. McDonald, A., Wasserman, E., Lengerich, E.J., Raman, J., Geyer, N., Hohl, R. and Wang, M. Prostate cancer incidence and aggressiveness in Appalachia versus Non-Appalachia population in Pennsylvania by urban-rural regions, 2004-2014.  The Journal of Cancer Epidemiology, Biomarkers & Prevention, 2020. doi: 10.1158/1055-9965.EPI-19-1232.

21. Bluethmann, SM., Wang, M., Wasserman, E., Chen, C.*, Zaorsky, N., Hohl, R. and McDonald, A. Prostate Cancer Survivorship: The Impact of Older Age at Diagnosis, Disease Aggressiveness and Behavioral Risk Factors on Treatment and Mortality. Cancer Medicine, 2020;9 (10): 3623-3633.

22. Li, H.*, Mukherjee, D., Krishnamurthy, V., Millett, C., Ryan, KA., Sauders, E+ and Wang, M.+. Use of ecological momentary assessment to detect variability in mood, sleep and stress in bipolar disorder. BMC Research Notes, 2019;12(1):791. doi: 10.1186/s13104-019-4834-7.

23. Wang, M., Chi, G., Bodovaki, Y., Holder, S., Lengerich, E., Wasserman, E. and McDonald, A. Spatial-temporal analysis of prostate cancer aggressiveness in Black and white Men from the Pennsylvania Cancer Registry, 2004-2014. Journal of Cancer Causes and Control, 2019;31(1): 63-71.

24. Wang, M.+, Long, Q. Chen, C.* and Zhang, L. Predictive accuracy measure of survival regressions subject to non-independent censoring. Statistics in Medicine, 2019; 39 (4): 469-480.

25. Chen, C.*, Jiang, L., Fu, G., Wang, M., Wang, Y., hen, B., Liu, Z., Wang, Z., Hou, W., Berceli, S. and Wu, R. A Unified Inference Theory of Personalized Gene Regulatory Networks. npj Syst Biol Appl, 2019; 5, 38. https://doi.org/10.1038/s41540-019-0116-1.

26. Li, Z.*, Chinchilli, VM. and Wang, M.+ A time-varying joint frailty-copula model for analyzing recurrent events and a terminal event: an application to the Cardiovascular Health Study. Journal of the Royal Statistical Society, Series C., 2019; 69(1):151-166.

27. Chen, C.*, Shen, B.*, Zhang, L., Xue, Y. and Wang, M+. Empirical-likelihood-based criteria for model selection on marginal analysis of longitudinal data with dropout missingness. Biometrics, 2019. https://doi.org/10.1111/biom.13060. (arXiv:1804.07430; Early version won Chixiang the 2018 International Chinese Statistical Association Applied Statistics Symposiums student paper award).

28. Ye, M., Jiang, L., Chen, C., Zhu, X., Wang, M. and Wu, R. mp2QTL: Networking phenotypic plasticity QTLs across heterogeneous environments. The Plant Journal, 2019. https://doi.org/10.1111/tpj.14355.

29. Li, Y., Wang, M. and Cheung K. Treatment Prioritization in Phase I Umbrella Protocol for Targeted Cancer Therapies. Journal of the Royal Statistical Society, Series C, 2018. DOI: 10.1111/rssc.12324.

30. Xu C*, Li Z*, Xue Y, Zhang L and Wang M.+ An R package for model fitting, model selection and the simulation for longitudinal data with dropout missingness. Communications in Statistics-Simulation and Computation, 2018. https://doi.org/10.1080/03610918.2018.1468457.

31. Li Z*, Chinchilli VM and Wang M.+ A Bayesian joint model of recurrent events and a terminal event. Biometrical Journal, 2018. https://doi.org/10.1002/bimj.201700326.

32. Xu C*, Chinchilli VM, Wang M.+ Joint modeling of recurrent events and a terminal event adjusted for zero inflation and a matched design. Stat Med. 2018 Aug 15; 37(18):2771-2786. PMID: 29682772.

33. Zhang L, Wang M, Sterling NW, Lee EY, Eslinger PJ, Wagner D, Du G, Lewis MM, Truong Y, Bowman FD, Huang X. Cortical Thinning and Cognitive Impairment in Parkinson's Disease without Dementia. IEEE/ACM Trans Comput Biol Bioinform. 2018 Mar-Apr; 15(2):570-580. PMID: 29610105. (Co-first author)

34. Wang M+, Matthews SA, Iskandarani K, Li Y, Li Z, Chinchilli VM, Zhang L. Spatial-temporal analysis of prostate cancer incidence from the Pennsylvania Cancer Registry, 2000-2011. Geospat Health. 2017 Nov 28; 12(2):611. PMID: 29239571.

35. Wang M+, Li Z*, Lee EY, Lewis MM, Zhang L, Sterling NW, Wagner D, Eslinger P, Du G, Huang X. Predicting the multi-domain progression of Parkinson's disease: a Bayesian multivariate generalized linear mixed-effect model. BMC Med Res Methodol. 2017 Sep 25; 17(1):147. PMID: 28946857.

36. Wang M+, Li Z*, Reeves B. RE: "RECEIVER OPERATING CHARACTERISTIC CURVE INFERENCE FROM A SAMPLE WITH A LIMIT OF DETECTION". Am J Epidemiol. 2016 10 01; 184(7):552-553. PMID: 27620450.

37. Peng L, Manatunga A, Wang M, Guo Y, Rahman AF. A general approach to categorizing a continuous scale according to an ordinal outcome. J Stat Plan Inference. 2016 May 01; 172:23-25. PMID: 26941475.

38. Wang M+, Long Q. Addressing issues associated with evaluating prediction models for survival endpoints based on the concordance statistic. Biometrics. 2016 Sep; 72(3):897-906. PMID: 26756274; PMCID: PMC4940324.

39. Wang M+, Kong L, Li Z*, Zhang L. Covariance estimators for generalized estimating equations (GEE) in longitudinal analysis with small samples. Stat Med. 2016 May 10; 35(10):1706-21. PMID: 26585756.

40. Wang M+, Luo J, Fu H, Qu Y. Piecewise Negative Binomial Regression in Analyzing Hypoglycemic Events with Missing Observations. J Biomet Biostat. 2014; 5(3):195.

41. Wang M+. Generalized Estimating Equations in Longitudinal Data Analysis: A Review and Recent Developments. Advances in Statistics, 2014. Article ID 303728. 11 pages.

42. Wang M+, Flanders WD, Bostick RM, Long Q. A conditional likelihood approach for regression analysis using biomarkers measured with batch-specific error. Stat Med. 2012 Dec 20; 31(29):3896-906. PMID: 22826173; PMCID: PMC3482310.

43. Wang M+, Zhang L. A Bayesian Quantile Regression Analysis of Potential Risk Factors for Violent Crimes in USA. Open Journal of Statistics. 2012; 2(5):526-533.

44. Wang M+, Long Q. Modified robust variance estimator for generalized estimating equations with improved small-sample performance. Stat Med. 2011 May 20; 30(11):1278-91. PMID: 21538453.

45. Wang M+, Kong M, Datta S. Inference for marginal linear models for clustered longitudinal data with potentially informative cluster sizes. Stat Methods Med Res. 2011 Aug; 20(4):347-67. PMID: 20223781.