Shuangge Steven Ma, PhD
Department Chair and Professor of Biostatistics; Affiliated Faculty, Yale Institute for Global Health; Director, Biostatistics and Bioinformatics Shared Resource
Research & Publications
Biography
News
Locations
Research Summary
I conduct independent research in multiple statistical areas, including bioinformatics, survival analysis, and semiparametric analysis with support from multiple funding agencies. I provide statistical support to multiple studies conducted at Yale and VA CT Healthcare System in the areas of cancer, mental disorders and health economics.
Extensive Research Description
Develop novel statistical methodologies for complex data;
Study epidemiology and pathogenesis of multiple cancers, including breast cancer, NHL, melanoma and lung cancer;
Conduct survey studies in mainland China and Taiwan, investigating health insurance utilization and impact;
Provide statistical support to multiple biomedical studies.
Research Interests
Economics; Neoplasms; Biostatistics
Public Health Interests
Bioinformatics; Biomarkers; Cancer; Cardiovascular Diseases; Genetics, Genomics, Epigenetics; Health Policy; Mental Health
Selected Publications
- Heterogeneous graphical model for non‐negative and non‐Gaussian PM2.5 dataZhang J, Fan X, Li Y, Ma S. Heterogeneous graphical model for non‐negative and non‐Gaussian PM2.5 data Journal Of The Royal Statistical Society Series C (Applied Statistics) 2022, 71: 1303-1329. DOI: 10.1111/rssc.12575.
- Biclustering analysis of functionals via penalized fusionFang K, Chen Y, Ma S, Zhang Q. Biclustering analysis of functionals via penalized fusion Journal Of Multivariate Analysis 2022, 189: 104874. DOI: 10.1016/j.jmva.2021.104874.
- Network-adaptive robust penalized estimation of time-varying coefficient models with longitudinal dataFang K, Fan X, Ma S, Zhang Q. Network-adaptive robust penalized estimation of time-varying coefficient models with longitudinal data Journal Of Statistical Computation And Simulation 2022, 92: 3045-3065. DOI: 10.1080/00949655.2022.2055758.
- A tree‐based gene–environment interaction analysis with rare featuresLiu M, Zhang Q, Ma S. A tree‐based gene–environment interaction analysis with rare features Statistical Analysis And Data Mining The ASA Data Science Journal 2022, 15: 648-674. DOI: 10.1002/sam.11578.
- An association test for functional data based on Kendall’s TauJadhav S, Ma S. An association test for functional data based on Kendall’s Tau Journal Of Multivariate Analysis 2021, 184: 104740. DOI: 10.1016/j.jmva.2021.104740.
- Promote sign consistency in the joint estimation of precision matricesZhang Q, Ma S, Huang Y. Promote sign consistency in the joint estimation of precision matrices Computational Statistics & Data Analysis 2021, 159: 107210. DOI: 10.1016/j.csda.2021.107210.
- Conditional score matching for high-dimensional partial graphical modelsFan X, Zhang Q, Ma S, Fang K. Conditional score matching for high-dimensional partial graphical models Computational Statistics & Data Analysis 2021, 153: 107066. DOI: 10.1016/j.csda.2020.107066.
- An Application of the Cure Model to a Cardiovascular Clinical TrialSevilimedu V, Ma S, Hartigan P, Kyriakides T. An Application of the Cure Model to a Cardiovascular Clinical Trial Statistics In Biosciences 2020, 13: 402-430. DOI: 10.1007/s12561-020-09297-w.
- Functional measurement error in functional regressionJadhav S, Ma S. Functional measurement error in functional regression Canadian Journal Of Statistics 2020, 48: 238-258. DOI: 10.1002/cjs.11529.
- A modified mean-variance feature-screening procedure for ultrahigh-dimensional discriminant analysisHe S, Ma S, Xu W. A modified mean-variance feature-screening procedure for ultrahigh-dimensional discriminant analysis Computational Statistics & Data Analysis 2019, 137: 155-169. DOI: 10.1016/j.csda.2019.02.003.
- Penalized Relative Error Estimation of a Partially Functional Linear Multiplicative ModelZhang T, Huang Y, Zhang Q, Ma S, Ahmed S. Penalized Relative Error Estimation of a Partially Functional Linear Multiplicative Model 2019, 127-144. DOI: 10.1007/978-3-030-17519-1_10.
- Variable selection and direction estimation for single-index models via DC-TGDR methodZhong W, Liu X, Ma S. Variable selection and direction estimation for single-index models via DC-TGDR method Statistics And Its Interface 2018, 11: 169-181. DOI: 10.4310/sii.2018.v11.n1.a14.
- 2432Huang Y, Brown S, Ma S, Kyriakides T. 2432 Journal Of Clinical And Translational Science 2017, 1: 37-37. PMCID: PMC6799711, DOI: 10.1017/cts.2017.137.
- Identifying Gene–Environment Interactions Associated with Prognosis Using Penalized Quantile RegressionWang G, Zhao Y, Zhang Q, Zang Y, Zang S, Ma S. Identifying Gene–Environment Interactions Associated with Prognosis Using Penalized Quantile Regression 2017, 347-367. DOI: 10.1007/978-3-319-41573-4_17.